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## A

abortExperiment() - Method in class weka.experiment.RemoteExperiment
  Set the abort flag
AbstractDataSink - Class in weka.gui.beans
  Abstract class for objects that store instances to some destination.
AbstractDataSink() - Constructor for class weka.gui.beans.AbstractDataSink
AbstractDataSinkBeanInfo - Class in weka.gui.beans
  Bean info class for the AbstractDataSink
AbstractDataSinkBeanInfo() - Constructor for class weka.gui.beans.AbstractDataSinkBeanInfo
AbstractDataSource - Class in weka.gui.beans
  Abstract class for objects that can provide instances from some source
AbstractDataSource() - Constructor for class weka.gui.beans.AbstractDataSource
  Creates a new `AbstractDataSource` instance.
AbstractDataSourceBeanInfo - Class in weka.gui.beans
  Bean info class for AbstractDataSource.
AbstractDataSourceBeanInfo() - Constructor for class weka.gui.beans.AbstractDataSourceBeanInfo
AbstractEvaluator - Class in weka.gui.beans
  Abstract class for objects that can provide some kind of evaluation for classifier, clusterers etc.
AbstractEvaluator() - Constructor for class weka.gui.beans.AbstractEvaluator
  Constructor
AbstractFileSaver - Class in weka.core.converters
  Abstract class for Savers that save to a file Valid options are: -i input arff file
  The input filw in arff format.
AbstractFileSaver() - Constructor for class weka.core.converters.AbstractFileSaver
AbstractLoader - Class in weka.core.converters
  Abstract class gives default implementation of setSource methods.
AbstractLoader() - Constructor for class weka.core.converters.AbstractLoader
AbstractSaver - Class in weka.core.converters
  Abstract class for Saver
AbstractSaver() - Constructor for class weka.core.converters.AbstractSaver
AbstractTestSetProducer - Class in weka.gui.beans
  Abstract class for TestSetProducers that contains default implementations of add/remove listener methods and defualt visual representation.
AbstractTestSetProducer() - Constructor for class weka.gui.beans.AbstractTestSetProducer
  Creates a new `AbstractTestSetProducer` instance.
AbstractTestSetProducerBeanInfo - Class in weka.gui.beans
  BeanInfo class for AbstractTestSetProducer
AbstractTestSetProducerBeanInfo() - Constructor for class weka.gui.beans.AbstractTestSetProducerBeanInfo
AbstractTimeSeries - Class in weka.filters.unsupervised.attribute
  An abstract instance filter that assumes instances form time-series data and performs some merging of attribute values in the current instance with attribute attribute values of some previous (or future) instance.
AbstractTimeSeries() - Constructor for class weka.filters.unsupervised.attribute.AbstractTimeSeries
AbstractTrainAndTestSetProducer - Class in weka.gui.beans
  Abstract base class for TrainAndTestSetProducers that contains default implementations of add/remove listener methods and defualt visual representation.
AbstractTrainAndTestSetProducer() - Constructor for class weka.gui.beans.AbstractTrainAndTestSetProducer
  Creates a new `AbstractTrainAndTestSetProducer` instance.
AbstractTrainAndTestSetProducerBeanInfo - Class in weka.gui.beans
  Bean info class for AbstractTrainAndTestSetProducers
AbstractTrainAndTestSetProducerBeanInfo() - Constructor for class weka.gui.beans.AbstractTrainAndTestSetProducerBeanInfo
AbstractTrainingSetProducer - Class in weka.gui.beans
  Abstract class for TrainingSetProducers that contains default implementations of add/remove listener methods and default visual representation
AbstractTrainingSetProducer() - Constructor for class weka.gui.beans.AbstractTrainingSetProducer
  Creates a new `AbstractTrainingSetProducer` instance.
AbstractTrainingSetProducerBeanInfo - Class in weka.gui.beans
  BeanInfo class for AbstractTrainingSetProducer
AbstractTrainingSetProducerBeanInfo() - Constructor for class weka.gui.beans.AbstractTrainingSetProducerBeanInfo
accept(File) - Method in class weka.gui.ExtensionFileFilter
  Returns true if the supplied file should be accepted (i.e.: if it has the required extension or is a directory).
accept(File, String) - Method in class weka.gui.ExtensionFileFilter
  Returns true if the file in the given directory with the given name should be accepted.
ACCEPT - Static variable in class weka.gui.treevisualizer.TreeDisplayEvent
  States that the user has accepted the tree.
acceptClassifier(BatchClassifierEvent) - Method in interface weka.gui.beans.BatchClassifierListener
  Accept a BatchClassifierEvent
acceptClassifier(BatchClassifierEvent) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator
  Accept a classifier to be evaluated
acceptClassifier(IncrementalClassifierEvent) - Method in class weka.gui.beans.IncrementalClassifierEvaluator
  Accepts and processes a classifier encapsulated in an incremental classifier event
acceptClassifier(IncrementalClassifierEvent) - Method in interface weka.gui.beans.IncrementalClassifierListener
  Accept the event
acceptClassifier(IncrementalClassifierEvent) - Method in class weka.gui.beans.PredictionAppender
  Accept and process an incremental classifier event
acceptClassifier(BatchClassifierEvent) - Method in class weka.gui.beans.PredictionAppender
  Accept and process a batch classifier event
acceptClusterer(BatchClustererEvent) - Method in interface weka.gui.beans.BatchClustererListener
  Accept a BatchClustererEvent
acceptClusterer(BatchClustererEvent) - Method in class weka.gui.beans.ClustererPerformanceEvaluator
  Accept a clusterer to be evaluated
acceptClusterer(BatchClustererEvent) - Method in class weka.gui.beans.PredictionAppender
  Accept and process a batch clusterer event
acceptDataPoint(ChartEvent) - Method in interface weka.gui.beans.ChartListener
acceptDataPoint(ChartEvent) - Method in class weka.gui.beans.StripChart
  Accept a data point (encapsulated in a chart event) to plot
acceptDataPoint(double[]) - Method in class weka.gui.beans.StripChart
  Accept a data point to plot
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.AbstractDataSink
  Accept a data set
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer
  Subclass must implement
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.ClassAssigner
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.ClassValuePicker
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.CrossValidationFoldMaker
  Accept a data set
acceptDataSet(DataSetEvent) - Method in interface weka.gui.beans.DataSourceListener
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.DataVisualizer
  Accept a data set
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.Filter
  Accept a data set
acceptDataSet(ThresholdDataEvent) - Method in class weka.gui.beans.ModelPerformanceChart
  Display a threshold curve.
acceptDataSet(VisualizableErrorEvent) - Method in class weka.gui.beans.ModelPerformanceChart
  Display a scheme error plot.
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.Saver
  Method reacts to a dataset event and starts the writing process in batch mode
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.TestSetMaker
  Accepts and processes a data set event
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.TextViewer
  Accept a data set for displaying as text
acceptDataSet(ThresholdDataEvent) - Method in interface weka.gui.beans.ThresholdDataListener
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.TrainingSetMaker
  Accept a data set
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.TrainTestSplitMaker
  Accept a data set
acceptDataSet(VisualizableErrorEvent) - Method in interface weka.gui.beans.VisualizableErrorListener
acceptGraph(GraphEvent) - Method in interface weka.gui.beans.GraphListener
  Describe `acceptGraph` method here.
acceptGraph(GraphEvent) - Method in class weka.gui.beans.GraphViewer
  Accept a graph
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.AbstractDataSink
  Accept an instance
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.ClassAssigner
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.Classifier
  Accepts an instance for incremental processing.
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.Filter
  Accept an instance for processing by StreamableFilters only
acceptInstance(InstanceEvent) - Method in interface weka.gui.beans.InstanceListener
  Accept and process an instance event
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.Saver
  Methods reacts to instance events and saves instances incrementally.
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.StripChart
acceptResult(ResultProducer, Object[], Object[]) - Method in class weka.experiment.AveragingResultProducer
  Accepts results from a ResultProducer.
acceptResult(ResultProducer, Object[], Object[]) - Method in class weka.experiment.CSVResultListener
  Just prints out each result as it is received.
acceptResult(ResultProducer, Object[], Object[]) - Method in class weka.experiment.DatabaseResultListener
  Submit the result to the appropriate table of the database
acceptResult(ResultProducer, Object[], Object[]) - Method in class weka.experiment.DatabaseResultProducer
  Accepts results from a ResultProducer.
acceptResult(ResultProducer, Object[], Object[]) - Method in class weka.experiment.InstancesResultListener
  Collects each instance and adjusts the header information.
acceptResult(ResultProducer, Object[], Object[]) - Method in class weka.experiment.LearningRateResultProducer
  Accepts results from a ResultProducer.
acceptResult(ResultProducer, Object[], Object[]) - Method in interface weka.experiment.ResultListener
  Accepts results from a ResultProducer.
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.AbstractDataSink
  Accept a test set
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.ClassAssigner
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.Classifier
  Accepts a test set for a batch trained classifier
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.Clusterer
  Accepts a test set for a batch trained clusterer
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.CrossValidationFoldMaker
  Accept a test set
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.DataVisualizer
  Accept a test set
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.Filter
  Accept a test set
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.Saver
  Method reacts to a test set event and starts the writing process in batch mode
acceptTestSet(TestSetEvent) - Method in interface weka.gui.beans.TestSetListener
  Accept and process a test set event
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.TextViewer
  Accept a test set for displaying as text
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.TrainTestSplitMaker
  Accept a test set
acceptText(TextEvent) - Method in interface weka.gui.beans.TextListener
  Accept and process a text event
acceptText(TextEvent) - Method in class weka.gui.beans.TextViewer
  Accept some text
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.AbstractDataSink
  Accept a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.ClassAssigner
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Classifier
  Accepts a training set and builds batch classifier
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Clusterer
  Accepts a training set and builds batch clusterer
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.CrossValidationFoldMaker
  Accept a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.DataVisualizer
  Accept a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Filter
  Accept a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Saver
  Method reacts to a training set event and starts the writing process in batch mode
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.TextViewer
  Accept a training set for displaying as text
acceptTrainingSet(TrainingSetEvent) - Method in interface weka.gui.beans.TrainingSetListener
  Accept and process a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.TrainTestSplitMaker
  Accept a training set
accuracy() - Method in class weka.associations.RuleItem
  Gets the expected predictive accuracy of a rule
actEntropy - Variable in class weka.classifiers.lazy.kstar.KStarWrapper
  used/reused to hold the actual entropy
actionPerformed(ActionEvent) - Method in class weka.gui.arffviewer.ArffPanel
  invoked when an action occurs
actionPerformed(ActionEvent) - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  invoked when an action occurs
actionPerformed(ActionEvent) - Method in class weka.gui.experiment.AlgorithmListPanel
  Handle actions when buttons get pressed.
actionPerformed(ActionEvent) - Method in class weka.gui.experiment.DatasetListPanel
  Handle actions when buttons get pressed.
actionPerformed(ActionEvent) - Method in class weka.gui.experiment.GeneratorPropertyIteratorPanel
  Handles the various button clicking type activities.
actionPerformed(ActionEvent) - Method in class weka.gui.experiment.HostListPanel
  Handle actions when text is entered into the host field or the delete button is pressed.
actionPerformed(ActionEvent) - Method in class weka.gui.experiment.RunPanel
  Controls starting and stopping the experiment.
actionPerformed(ActionEvent) - Method in class weka.gui.SimpleCLI
  Only gets called when return is pressed in the input area, which starts the command running.
actionPerformed(ActionEvent) - Method in class weka.gui.streams.InstanceLoader
actionPerformed(ActionEvent) - Method in class weka.gui.treevisualizer.TreeVisualizer
  Performs the action associated with the ActionEvent.
actual() - Method in class weka.classifiers.evaluation.NominalPrediction
  Gets the actual class value.
actual() - Method in class weka.classifiers.evaluation.NumericPrediction
  Gets the actual class value.
actual() - Method in interface weka.classifiers.evaluation.Prediction
  Gets the actual class value.
actualNumBags() - Method in class weka.classifiers.trees.j48.Distribution
  Returns number of non-empty bags of distribution.
actualNumClasses() - Method in class weka.classifiers.trees.j48.Distribution
  Returns number of classes actually occuring in distribution.
actualNumClasses(int) - Method in class weka.classifiers.trees.j48.Distribution
  Returns number of classes actually occuring in given bag.
acuityTipText() - Method in class weka.clusterers.Cobweb
  Returns the tip text for this property
AdaBoostM1 - Class in weka.classifiers.meta
  Class for boosting a classifier using Freund & Schapire's Adaboost M1 method.
AdaBoostM1() - Constructor for class weka.classifiers.meta.AdaBoostM1
  Constructor.
add(Object) - Method in class weka.associations.tertius.SimpleLinkedList
add(int, Instance) - Method in class weka.classifiers.trees.j48.Distribution
  Adds given instance to given bag.
add(int, double[]) - Method in class weka.classifiers.trees.j48.Distribution
  Adds counts to given bag.
add(Instance) - Method in class weka.core.Instances
  Adds one instance to the end of the set.
add(Matrix) - Method in class weka.core.Matrix
  Deprecated. Returns the sum of this matrix with another.
add(String, Method) - Method in class weka.core.xml.MethodHandler
  adds the specified method for the property with the given displayname to its internal list.
add(Class, Method) - Method in class weka.core.xml.MethodHandler
  adds the specified method for the given class to its internal list.
add(double, double) - Method in class weka.experiment.PairedStats
  Add an observed pair of values.
add(double) - Method in class weka.experiment.Stats
  Adds a value to the observed values
add(double, double) - Method in class weka.experiment.Stats
  Adds a value that has been seen n times to the observed values
Add - Class in weka.filters.unsupervised.attribute
  An instance filter that adds a new attribute to the dataset.
Add() - Constructor for class weka.filters.unsupervised.attribute.Add
add(String) - Method in class weka.gui.HierarchyPropertyParser
  Add the given item of property to the tree
ADD_CHILDREN - Static variable in class weka.gui.treevisualizer.TreeDisplayEvent
addActionListener(ActionListener) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel
  Register a listener to be notified when plotting completes
addActionListener(ActionListener) - Method in class weka.gui.experiment.GeneratorPropertyIteratorPanel
  Add a listener interested in kowing about editor status changes
addActionListener(ActionListener) - Method in class weka.gui.visualize.ClassPanel
  Add an action listener that will be notified if the user changes the colour of a label
addActionListener(ActionListener) - Method in class weka.gui.visualize.VisualizePanel
  Add a listener for this visualize panel
addAll(SimpleLinkedList) - Method in class weka.associations.tertius.SimpleLinkedList
addAllBeansToContainer(JComponent) - Static method in class weka.gui.beans.BeanInstance
  Adds all beans to the supplied component
addAllowed(Class, String) - Method in class weka.core.xml.PropertyHandler
  adds the given property (display name) to the list of allowed properties for the specified class.
addAndUpdate(Rule) - Method in class weka.classifiers.rules.RuleStats
  Add a rule to the ruleset and update the stats
addAttributePanelListener(AttributePanelListener) - Method in class weka.gui.visualize.AttributePanel
  Add a listener to the list of things listening to this panel
addBatchClassifierListener(BatchClassifierListener) - Method in class weka.gui.beans.Classifier
  Add a batch classifier listener
addBatchClustererListener(BatchClustererListener) - Method in class weka.gui.beans.Clusterer
  Add a batch clusterer listener
addBean(JComponent) - Method in class weka.gui.beans.BeanInstance
  Adds this bean to the global list of beans and to the supplied container.
addBefore(Object) - Method in class weka.associations.tertius.SimpleLinkedList.LinkedListIterator
addCancelListener(ActionListener) - Method in class weka.gui.GenericObjectEditor.GOEPanel
  This is used to hook an action listener to the cancel button
addChangeListener(ChangeListener) - Method in class weka.gui.arffviewer.ArffPanel
  Adds a ChangeListener to the panel
addChangeListener(ChangeListener) - Method in class weka.gui.arffviewer.ArffTable
  Adds a ChangeListener to the panel
addChartListener(ChartListener) - Method in class weka.gui.beans.IncrementalClassifierEvaluator
  Add a chart listener
addCheckBoxActionListener(ActionListener) - Method in class weka.gui.experiment.DistributeExperimentPanel
  Enable objects to listen for changes to the check box
addChild(Splitter, ADTree) - Method in class weka.classifiers.trees.adtree.PredictionNode
  Adds a child to this node.
addChild(Edge) - Method in class weka.gui.treevisualizer.Node
  Set the value of children.
AddCluster - Class in weka.filters.unsupervised.attribute
  A filter that adds a new nominal attribute representing the cluster assigned to each instance by the specified clustering algorithm.
AddCluster() - Constructor for class weka.filters.unsupervised.attribute.AddCluster
addCons(int[]) - Method in class weka.associations.PriorEstimation
  generates a class association rule out of a given premise.
addCVParameter(String) - Method in class weka.classifiers.meta.CVParameterSelection
  Adds a scheme parameter to the list of parameters to be set by cross-validation
addDataFormatListener(DataFormatListener) - Method in class weka.gui.beans.ClassAssigner
addDataFormatListener(DataFormatListener) - Method in class weka.gui.beans.ClassValuePicker
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.AbstractDataSource
  Add a listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.ClassAssigner
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.ClassValuePicker
addDataSourceListener(DataSourceListener) - Method in interface weka.gui.beans.DataSource
  Add a data source listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Filter
  Add a data source listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Loader
  Add a listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.PredictionAppender
  Add a datasource listener
addElement(Literal) - Method in class weka.associations.tertius.LiteralSet
  Add a Literal to this set.
addElement(double) - Method in class weka.classifiers.functions.pace.DoubleVector
  Adds an element into the vector
addElement(Object) - Method in class weka.core.FastVector
  Adds an element to this vector.
addElement(int, int, double) - Method in class weka.core.Matrix
  Deprecated. Add a value to an element.
addErrs(double, double, float) - Static method in class weka.classifiers.trees.j48.Stats
  Computes estimated extra error for given total number of instances and error using normal approximation to binomial distribution (and continuity correction).
AddExpression - Class in weka.filters.unsupervised.attribute
  Applys a mathematical expression involving attributes and numeric constants to a dataset.
AddExpression() - Constructor for class weka.filters.unsupervised.attribute.AddExpression
addFirst(Object) - Method in class weka.associations.tertius.SimpleLinkedList
addGraphListener(GraphListener) - Method in class weka.gui.beans.Classifier
  Add a graph listener
addGraphListener(GraphListener) - Method in class weka.gui.beans.Clusterer
  Add a graph listener
addIgnored(String) - Method in class weka.core.xml.PropertyHandler
  adds the given display name of a property to the ignore list.
addIgnored(Class, String) - Method in class weka.core.xml.PropertyHandler
  adds the given class with the display name of a property to the ignore list.
addIncrementalClassifierListener(IncrementalClassifierListener) - Method in class weka.gui.beans.Classifier
  Add an incremental classifier listener
addInstance(Instance) - Method in class weka.clusterers.Cobweb
  Adds an instance to the Cobweb tree.
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.AbstractDataSource
  Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.ClassAssigner
addInstanceListener(InstanceListener) - Method in interface weka.gui.beans.DataSource
  Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.Filter
  Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.Loader
  Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.PredictionAppender
  Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.streams.InstanceJoiner
addInstanceListener(InstanceListener) - Method in class weka.gui.streams.InstanceLoader
addInstanceListener(InstanceListener) - Method in interface weka.gui.streams.InstanceProducer
addInstanceNumberAttribute() - Method in class weka.gui.visualize.PlotData2D
  Adds an instance number attribute to the plottable instances,
addInstWithUnknown(Instances, int) - Method in class weka.classifiers.trees.j48.Distribution
  Adds all instances with unknown values for given attribute, weighted according to frequency of instances in each bag.
AdditionalMeasureProducer - Interface in weka.core
  Interface to something that can produce measures other than those calculated by evaluation modules.
AdditiveRegression - Class in weka.classifiers.meta
  Meta classifier that enhances the performance of a regression base classifier.
AdditiveRegression() - Constructor for class weka.classifiers.meta.AdditiveRegression
  Default constructor specifying DecisionStump as the classifier
AdditiveRegression(Classifier) - Constructor for class weka.classifiers.meta.AdditiveRegression
  Constructor which takes base classifier as argument.
addLayoutCompleteEventListener(LayoutCompleteEventListener) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine
  Method to add a LayoutCompleteEventListener
addLayoutCompleteEventListener(LayoutCompleteEventListener) - Method in interface weka.gui.graphvisualizer.LayoutEngine
  This method adds a LayoutCompleteEventListener to the LayoutEngine.
addLiteral(Literal) - Method in class weka.associations.tertius.Predicate
addMouseListenerToHeaderInTable(JTable) - Method in class weka.gui.TableSorter
AddNoise - Class in weka.filters.unsupervised.attribute
  Introduces noise data a random subsample of the dataset by changing a given attribute (attribute must be nominal) Valid options are:
AddNoise() - Constructor for class weka.filters.unsupervised.attribute.AddNoise
addNoise(Instances, int, int, int, boolean) - Method in class weka.filters.unsupervised.attribute.AddNoise
  add noise to the dataset a given percentage of the instances are changed in the way, that a set of instances are randomly selected using seed.
addObject(String, Object) - Method in class weka.gui.ResultHistoryPanel
  Adds an object to the results list
addOkListener(ActionListener) - Method in class weka.gui.GenericObjectEditor.GOEPanel
  This is used to hook an action listener to the ok button
addParent(int, Instances) - Method in class weka.classifiers.bayes.net.ParentSet
  Add parent to parent set and update internals (specifically the cardinality of the parent set)
addParent(int, int, Instances) - Method in class weka.classifiers.bayes.net.ParentSet
  Add parent to parent set at specific location and update internals (specifically the cardinality of the parent set)
addPlot(PlotData2D) - Method in class weka.gui.visualize.Plot2D
  Add a plot to the list of plots to display
addPlot(PlotData2D) - Method in class weka.gui.visualize.VisualizePanel
  Set a new plot to the visualize panel
addPrediction(NominalPrediction) - Method in class weka.classifiers.evaluation.ConfusionMatrix
  Includes a prediction in the confusion matrix.
addPredictions(FastVector) - Method in class weka.classifiers.evaluation.ConfusionMatrix
  Includes a whole bunch of predictions in the confusion matrix.
addPropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.AbstractDataSource
  Add a property change listener to this bean
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.BeanVisual
  Add a listener for property change events
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClassAssignerCustomizer
  Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClassifierCustomizer
  Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClassValuePickerCustomizer
  Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClustererCustomizer
  Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.CrossValidationFoldMakerCustomizer
  Add a property change listener
addPropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.DataVisualizer
  Add a property change listener to this bean
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.FilterCustomizer
  Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.LoaderCustomizer
  Add a property change listener
addPropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.ModelPerformanceChart
  Add a property change listener to this bean
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.PredictionAppenderCustomizer
  Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.SaverCustomizer
  Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.StripChartCustomizer
  Add a property change listener
addPropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.TextViewer
  Add a property change listener to this bean
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.TrainTestSplitMakerCustomizer
  Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.CostMatrixEditor
  Adds an object to the list of those that wish to be informed when the cost matrix changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.experiment.SetupModePanel
  Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.experiment.SetupPanel
  Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.experiment.SimpleSetupPanel
  Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.explorer.PreprocessPanel
  Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.GenericArrayEditor
  Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.GenericObjectEditor
  Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.PropertySheetPanel
  Adds a PropertyChangeListener.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.SetInstancesPanel
  Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.SimpleDateFormatEditor
  Adds an object to the list of those that wish to be informed when the date format changes.
addPropertyChangeListenersSubFlow(PropertyChangeListener) - Method in class weka.gui.beans.MetaBean
addPSFontReplacement(String, String) - Static method in class weka.gui.visualize.PostscriptGraphics
  adds the PS font name to replace and its replacement in the replacement hashtable
addRange(int, Instances, int, int) - Method in class weka.classifiers.trees.j48.Distribution
  Adds all instances in given range to given bag.
addReference(Instance) - Method in class weka.classifiers.trees.adtree.ReferenceInstances
  Adds one instance reference to the end of the set.
addRemoteExperimentListener(RemoteExperimentListener) - Method in class weka.experiment.RemoteExperiment
  Add an object to the list of those interested in recieving update information from the RemoteExperiment
addRemoteExperimentListener(RemoteExperimentListener) - Method in class weka.gui.boundaryvisualizer.BoundaryPanelDistributed
  Add an object to the list of those interested in recieving update information from the RemoteExperiment
addRemoteHost(String) - Method in class weka.experiment.RemoteExperiment
  Add a host name to the list of remote hosts
addRenderingHints(Map) - Method in class weka.gui.visualize.PostscriptGraphics
addRepaintNotify(Component) - Method in class weka.gui.visualize.ClassPanel
  Adds a component that will need to be repainted if the user changes the colour of a label.
addRepaintNotify(Component) - Method in class weka.gui.visualize.LegendPanel
  Adds a component that will need to be repainted if the user changes the colour of a label.
addResult(String, StringBuffer) - Method in class weka.gui.ResultHistoryPanel
  Adds a new result to the result list.
addStartupListener(StartUpListener) - Static method in class weka.gui.beans.KnowledgeFlowApp
  Add a listener to be notified when startup is complete
addStringValue(String) - Method in class weka.core.Attribute
  Adds a string value to the list of valid strings for attributes of type STRING and returns the index of the string.
addStringValue(Attribute, int) - Method in class weka.core.Attribute
  Adds a string value to the list of valid strings for attributes of type STRING and returns the index of the string.
addTableModelListener(TableModelListener) - Method in class weka.gui.arffviewer.ArffTableModel
  adds a listener to the list that is notified each time a change to data model occurs
addTableModelListener(TableModelListener) - Method in class weka.gui.arffviewer.ArffTableSorter
  adds a listener to the list that is notified each time a change to data model occurs
addTestSetListener(TestSetListener) - Method in class weka.gui.beans.AbstractTestSetProducer
  Add a listener for test sets
addTestSetListener(TestSetListener) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer
  Add a test set listener
addTestSetListener(TestSetListener) - Method in class weka.gui.beans.ClassAssigner
addTestSetListener(TestSetListener) - Method in class weka.gui.beans.Filter
  Add a test set listener
addTestSetListener(TestSetListener) - Method in class weka.gui.beans.PredictionAppender
  Add a test set listener
addTestSetListener(TestSetListener) - Method in interface weka.gui.beans.TestSetProducer
  Add a listener for test set events
addTextListener(TextListener) - Method in class weka.gui.beans.Classifier
  Add a text listener
addTextListener(TextListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator
  Add a text listener
addTextListener(TextListener) - Method in class weka.gui.beans.Clusterer
  Add a text listener
addTextListener(TextListener) - Method in class weka.gui.beans.ClustererPerformanceEvaluator
  Add a text listener
addTextListener(TextListener) - Method in class weka.gui.beans.IncrementalClassifierEvaluator
  Add a text listener
addThresholdDataListener(ThresholdDataListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator
  Add a threshold data listener
addToList(Object[], double) - Method in class weka.attributeSelection.BestFirst.LinkedList2
  adds an element (Link) to the list.
addToList(BitSet, double) - Method in class weka.classifiers.rules.DecisionTable.LinkedList
  Aadds an element (Link) to the list.
addTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer
  Add a training set listener
addTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.AbstractTrainingSetProducer
  Add a training set listener
addTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.ClassAssigner
addTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.Filter
  Add a training set listener
addTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.PredictionAppender
  Add a training set listener
addTrainingSetListener(TrainingSetListener) - Method in interface weka.gui.beans.TrainingSetProducer
  Add a training set listener
addUndoPoint() - Method in interface weka.core.Undoable
  adds an undo point to the undo history
addUndoPoint() - Method in class weka.gui.arffviewer.ArffPanel
  adds the current state of the instances to the undolist
addUndoPoint() - Method in class weka.gui.arffviewer.ArffTableModel
  adds an undo point to the undo history, if the undo support is enabled
addUndoPoint() - Method in class weka.gui.arffviewer.ArffTableSorter
  adds an undo point to the undo history
addUndoPoint() - Method in class weka.gui.explorer.PreprocessPanel
  Backs up the current state of the dataset, so the changes can be undone.
addValue(double, double) - Method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes
  Add a new data value to the current estimator.
addValue(double, double, double) - Method in interface weka.estimators.ConditionalEstimator
  Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.DDConditionalEstimator
  Add a new data value to the current estimator.
addValue(double, double) - Method in class weka.estimators.DiscreteEstimator
  Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.DKConditionalEstimator
  Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.DNConditionalEstimator
  Add a new data value to the current estimator.
addValue(double, double) - Method in interface weka.estimators.Estimator
  Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.KDConditionalEstimator
  Add a new data value to the current estimator.
addValue(double, double) - Method in class weka.estimators.KernelEstimator
  Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.KKConditionalEstimator
  Add a new data value to the current estimator.
addValue(double, double) - Method in class weka.estimators.MahalanobisEstimator
  Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.NDConditionalEstimator
  Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.NNConditionalEstimator
  Add a new data value to the current estimator.
addValue(double, double) - Method in class weka.estimators.NormalEstimator
  Add a new data value to the current estimator.
addValue(double, double) - Method in class weka.estimators.PoissonEstimator
  Add a new data value to the current estimator.
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.AbstractDataSource
  Add a vetoable change listener to this bean
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.DataVisualizer
  Add a vetoable change listener to this bean
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.ModelPerformanceChart
  Add a vetoable change listener to this bean
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.TextViewer
  Add a vetoable change listener to this bean
addVisualizableErrorListener(VisualizableErrorListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator
  Add a visualizable error listener
addWeights(Instance, double[]) - Method in class weka.classifiers.trees.j48.Distribution
  Adds given instance to all bags weighting it according to given weights.
adjustCenter(double) - Method in class weka.gui.treevisualizer.Node
  Will increase or decrease the postion of center.
adjustWeightsTipText() - Method in class weka.filters.supervised.instance.SpreadSubsample
  Returns the tip text for this property
ADNode - Class in weka.classifiers.bayes.net
  The ADNode class implements the ADTree datastructure which increases the speed with which sub-contingency tables can be constructed from a data set in an Instances object.
ADNode() - Constructor for class weka.classifiers.bayes.net.ADNode
  Creates new ADNode
ADTree - Class in weka.classifiers.trees
  Class for generating an alternating decision tree.
ADTree() - Constructor for class weka.classifiers.trees.ADTree
advanceCounters() - Method in class weka.experiment.Experiment
  Increments iteration counters appropriately.
advanceCounters() - Method in class weka.experiment.RemoteExperiment
  overides the one in Experiment
AIC - Static variable in interface weka.classifiers.bayes.net.search.local.Scoreable
AlgorithmListPanel - Class in weka.gui.experiment
  This panel controls setting a list of algorithms for an experiment to iterate over.
AlgorithmListPanel(Experiment) - Constructor for class weka.gui.experiment.AlgorithmListPanel
  Creates the algorithm list panel with the given experiment.
AlgorithmListPanel() - Constructor for class weka.gui.experiment.AlgorithmListPanel
  Create the algorithm list panel initially disabled.
AlgorithmListPanel.ObjectCellRenderer - Class in weka.gui.experiment
AlgorithmListPanel.ObjectCellRenderer() - Constructor for class weka.gui.experiment.AlgorithmListPanel.ObjectCellRenderer
AllFilter - Class in weka.filters
  A simple instance filter that passes all instances directly through.
AllFilter() - Constructor for class weka.filters.AllFilter
allowed() - Method in class weka.core.xml.PropertyHandler
  returns an enumeration of the classnames for which only certain properties (display names) are allowed
alphaTipText() - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator
alphaTipText() - Method in class weka.classifiers.functions.Winnow
  Returns the tip text for this property
AODE - Class in weka.classifiers.bayes
  AODE achieves highly accurate classification by averaging over all of a small space of alternative naive-Bayes-like models that have weaker (and hence less detrimental) independence assumptions than naive Bayes.
AODE() - Constructor for class weka.classifiers.bayes.AODE
appendElements(FastVector) - Method in class weka.core.FastVector
  Appends all elements of the supplied vector to this vector.
appendPredictedProbabilitiesTipText() - Method in class weka.gui.beans.PredictionAppender
  Return a tip text suitable for displaying in a GUI
applyCostMatrix(Instances, Random) - Method in class weka.classifiers.CostMatrix
  Applies the cost matrix to a set of instances.
APPROVE_OPTION - Static variable in class weka.gui.experiment.OutputFormatDialog
  Signifies an OK property selection
APPROVE_OPTION - Static variable in class weka.gui.ListSelectorDialog
  Signifies an OK property selection
APPROVE_OPTION - Static variable in class weka.gui.PropertySelectorDialog
  Signifies an OK property selection
APPROVE_OPTION - Static variable in class weka.gui.ViewerDialog
  Signifies an OK property selection
Apriori - Class in weka.associations
  Class implementing an Apriori-type algorithm.
Apriori() - Constructor for class weka.associations.Apriori
  Constructor that allows to sets default values for the minimum confidence and the maximum number of rules the minimum confidence.
AprioriItemSet - Class in weka.associations
  Class for storing a set of items.
AprioriItemSet(int) - Constructor for class weka.associations.AprioriItemSet
  Constructor
ArffLoader - Class in weka.core.converters
  Reads a source that is in arff text format.
ArffLoader() - Constructor for class weka.core.converters.ArffLoader
ArffPanel - Class in weka.gui.arffviewer
  A Panel representing an ARFF-Table and the associated filename.
ArffPanel() - Constructor for class weka.gui.arffviewer.ArffPanel
  initializes the panel with no data
ArffPanel(String) - Constructor for class weka.gui.arffviewer.ArffPanel
  initializes the panel and loads the specified file
ArffPanel(Instances) - Constructor for class weka.gui.arffviewer.ArffPanel
  initializes the panel with the given data
ArffSaver - Class in weka.core.converters
  Writes to a destination in arff text format.
ArffSaver() - Constructor for class weka.core.converters.ArffSaver
  Constructor
ArffTable - Class in weka.gui.arffviewer
  A specialized JTable for the Arff-Viewer.
ArffTable() - Constructor for class weka.gui.arffviewer.ArffTable
  initializes with no model
ArffTable(TableModel) - Constructor for class weka.gui.arffviewer.ArffTable
  initializes with the given model
ArffTableCellRenderer - Class in weka.gui.arffviewer
  Handles the background colors for missing values differently than the DefaultTableCellRenderer.
ArffTableCellRenderer() - Constructor for class weka.gui.arffviewer.ArffTableCellRenderer
  initializes the Renderer with a standard color
ArffTableCellRenderer(Color, Color) - Constructor for class weka.gui.arffviewer.ArffTableCellRenderer
  initializes the Renderer with the given colors
ArffTableCellRenderer(Color, Color, Color, Color) - Constructor for class weka.gui.arffviewer.ArffTableCellRenderer
  initializes the Renderer with the given colors
ArffTableModel - Class in weka.gui.arffviewer
  The model for the Arff-Viewer.
ArffTableModel(String) - Constructor for class weka.gui.arffviewer.ArffTableModel
  initializes the object and loads the given file
ArffTableModel(Instances) - Constructor for class weka.gui.arffviewer.ArffTableModel
  initializes the model with the given data
ArffTableSorter - Class in weka.gui.arffviewer
  A sorter for the ARFF-Viewer - necessary because of the custom CellRenderer.
ArffTableSorter(String) - Constructor for class weka.gui.arffviewer.ArffTableSorter
  initializes the sorter w/o a model, but loads the given file and creates from that a model
ArffTableSorter(Instances) - Constructor for class weka.gui.arffviewer.ArffTableSorter
  initializes the sorter w/o a model, but uses the given data to create a model from that
ArffTableSorter(TableModel) - Constructor for class weka.gui.arffviewer.ArffTableSorter
  initializes the sorter with the given model
ArffViewer - Class in weka.gui.arffviewer
  A little tool for viewing ARFF files.
ArffViewer() - Constructor for class weka.gui.arffviewer.ArffViewer
  initializes the object
ArffViewerMainPanel - Class in weka.gui.arffviewer
  The main panel of the ArffViewer.
ArffViewerMainPanel(JFrame) - Constructor for class weka.gui.arffviewer.ArffViewerMainPanel
  initializes the object
arrayLeftDivide(Matrix) - Method in class weka.classifiers.functions.pace.Matrix
  Element-by-element left division, C = A.\B
arrayLeftDivide(Matrix) - Method in class weka.core.matrix.Matrix
  Element-by-element left division, C = A.\B
arrayLeftDivideEquals(Matrix) - Method in class weka.classifiers.functions.pace.Matrix
  Element-by-element left division in place, A = A.\B
arrayLeftDivideEquals(Matrix) - Method in class weka.core.matrix.Matrix
  Element-by-element left division in place, A = A.\B
arrayRightDivide(Matrix) - Method in class weka.classifiers.functions.pace.Matrix
  Element-by-element right division, C = A./B
arrayRightDivide(Matrix) - Method in class weka.core.matrix.Matrix
  Element-by-element right division, C = A./B
arrayRightDivideEquals(Matrix) - Method in class weka.classifiers.functions.pace.Matrix
  Element-by-element right division in place, A = A./B
arrayRightDivideEquals(Matrix) - Method in class weka.core.matrix.Matrix
  Element-by-element right division in place, A = A./B
arrayTimes(Matrix) - Method in class weka.classifiers.functions.pace.Matrix
  Element-by-element multiplication, C = A.*B
arrayTimes(Matrix) - Method in class weka.core.matrix.Matrix
  Element-by-element multiplication, C = A.*B
arrayTimesEquals(Matrix) - Method in class weka.classifiers.functions.pace.Matrix
  Element-by-element multiplication in place, A = A.*B
arrayTimesEquals(Matrix) - Method in class weka.core.matrix.Matrix
  Element-by-element multiplication in place, A = A.*B
arrayToString(Object) - Static method in class weka.core.Utils
  Returns the given Array in a string representation.
arrayToString(Object[]) - Static method in class weka.experiment.DatabaseUtils
  Converts an array of objects to a string by inserting a space between each element.
artificialSizeTipText() - Method in class weka.classifiers.meta.Decorate
  Returns the tip text for this property
ASEvaluation - Class in weka.attributeSelection
  Abstract attribute selection evaluation class
ASEvaluation() - Constructor for class weka.attributeSelection.ASEvaluation
ASSearch - Class in weka.attributeSelection
  Abstract attribute selection search class.
ASSearch() - Constructor for class weka.attributeSelection.ASSearch
assignIDs(int) - Method in class weka.classifiers.trees.j48.ClassifierTree
  Assigns a uniqe id to every node in the tree.
assignIDs(int) - Method in class weka.classifiers.trees.lmt.LMTNode
  Assigns unique IDs to all nodes in the tree
assignLeafModelNumbers(int) - Method in class weka.classifiers.trees.lmt.LMTNode
  Assigns numbers to the logistic regression models at the leaves of the tree
associatedConnections(Vector) - Static method in class weka.gui.beans.BeanConnection
  Returns a vector of BeanConnections associated with the supplied vector of BeanInstances, i.e.
AssociationsPanel - Class in weka.gui.explorer
  This panel allows the user to select, configure, and run a scheme that learns associations.
AssociationsPanel() - Constructor for class weka.gui.explorer.AssociationsPanel
  Creates the associator panel
Associator - Class in weka.associations
  Abstract scheme for learning associations.
Associator() - Constructor for class weka.associations.Associator
aSubsumesB(RuleItem, RuleItem) - Static method in class weka.associations.RuleGeneration
  Methods that decides whether or not rule a subsumes rule b.
ATT_ARRAY - Static variable in class weka.core.xml.XMLSerialization
  the tag whether array or not (yes/no)
ATT_ARRAY_DEFAULT - Static variable in class weka.core.xml.XMLSerialization
  default value for attribute ATT_ARRAY
ATT_CLASS - Static variable in class weka.core.xml.XMLSerialization
  the tag for the class
ATT_NAME - Static variable in class weka.core.xml.XMLOptions
  the name attribute
ATT_NAME - Static variable in class weka.core.xml.XMLSerialization
  the tag for the name
ATT_NULL - Static variable in class weka.core.xml.XMLSerialization
  the tag whether null or not (yes/no)
ATT_NULL_DEFAULT - Static variable in class weka.core.xml.XMLSerialization
  default value for attribute ATT_NULL
ATT_PRIMITIVE - Static variable in class weka.core.xml.XMLSerialization
  the tag whether primitive or not (yes/no)
ATT_PRIMITIVE_DEFAULT - Static variable in class weka.core.xml.XMLSerialization
  default value for attribute ATT_PRIMITIVE
ATT_TYPE - Static variable in class weka.core.xml.XMLOptions
  the type attribute
ATT_VALUE - Static variable in class weka.core.xml.XMLOptions
  the value attribute
ATT_VERSION - Static variable in class weka.core.xml.XMLSerialization
  the version attribute
attIndex() - Method in class weka.classifiers.trees.j48.BinC45Split
  Returns index of attribute for which split was generated.
attIndex() - Method in class weka.classifiers.trees.j48.C45Split
  Returns index of attribute for which split was generated.
attIndex() - Method in class weka.classifiers.trees.j48.NBTreeSplit
  Returns index of attribute for which split was generated.
attIndexSetTipText() - Method in class weka.filters.unsupervised.attribute.AddNoise
  Returns the tip text for this property
Attribute - Class in weka.core
  Class for handling an attribute.
Attribute(String) - Constructor for class weka.core.Attribute
  Constructor for a numeric attribute.
Attribute(String, ProtectedProperties) - Constructor for class weka.core.Attribute
  Constructor for a numeric attribute, where metadata is supplied.
Attribute(String, String) - Constructor for class weka.core.Attribute
  Constructor for a date attribute.
Attribute(String, String, ProtectedProperties) - Constructor for class weka.core.Attribute
  Constructor for a date attribute, where metadata is supplied.
Attribute(String, FastVector) - Constructor for class weka.core.Attribute
  Constructor for nominal attributes and string attributes.
Attribute(String, FastVector, ProtectedProperties) - Constructor for class weka.core.Attribute
  Constructor for nominal attributes and string attributes, where metadata is supplied.
attribute(int) - Method in class weka.core.Instance
  Returns the attribute with the given index.
attribute(int) - Method in class weka.core.Instances
  Returns an attribute.
attribute(String) - Method in class weka.core.Instances
  Returns an attribute given its name.
AttributeEvaluator - Class in weka.attributeSelection
  Abstract attribute evaluator.
AttributeEvaluator() - Constructor for class weka.attributeSelection.AttributeEvaluator
attributeEvaluatorTipText() - Method in class weka.attributeSelection.RaceSearch
  Returns the tip text for this property
attributeEvaluatorTipText() - Method in class weka.attributeSelection.RankSearch
  Returns the tip text for this property
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.Add
  Returns the tip text for this property
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.MakeIndicator
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.StringToNominal
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.SwapValues
attributeIndexTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithValues
  Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.supervised.attribute.Discretize
  Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries
  Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.Copy
  Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.Discretize
  Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.FirstOrder
  Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.NominalToBinary
  Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.NumericTransform
  Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.Remove
  Returns the tip text for this property
AttributeListPanel - Class in weka.gui
  Creates a panel that displays the attributes contained in a set of instances, letting the user select a single attribute for inspection.
AttributeListPanel() - Constructor for class weka.gui.AttributeListPanel
  Creates the attribute selection panel with no initial instances.
attributeNamePrefixTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Returns the tip text for this property
attributeNames() - Method in class weka.classifiers.functions.SMO
  Returns the attribute names.
attributeNameTipText() - Method in class weka.filters.unsupervised.attribute.Add
  Returns the tip text for this property
AttributePanel - Class in weka.gui.visualize
  This panel displays one dimensional views of the attributes in a dataset.
AttributePanel() - Constructor for class weka.gui.visualize.AttributePanel
  This constructs an attributePanel.
AttributePanelEvent - Class in weka.gui.visualize
  Class encapsulating a change in the AttributePanel's selected x and y attributes.
AttributePanelEvent(boolean, boolean, int) - Constructor for class weka.gui.visualize.AttributePanelEvent
  Constructor
AttributePanelListener - Interface in weka.gui.visualize
  Interface for classes that want to listen for Attribute selection changes in the attribute panel
AttributeSelectedClassifier - Class in weka.classifiers.meta
  Class for running an arbitrary classifier on data that has been reduced through attribute selection.
AttributeSelectedClassifier() - Constructor for class weka.classifiers.meta.AttributeSelectedClassifier
  Default constructor.
AttributeSelection - Class in weka.attributeSelection
  Attribute selection class.
AttributeSelection() - Constructor for class weka.attributeSelection.AttributeSelection
  constructor.
AttributeSelection - Class in weka.filters.supervised.attribute
  Filter for doing attribute selection.
AttributeSelection() - Constructor for class weka.filters.supervised.attribute.AttributeSelection
  Constructor
attributeSelectionChange(AttributePanelEvent) - Method in interface weka.gui.visualize.AttributePanelListener
  Called when the user clicks on an attribute bar
attributeSelectionMethodTipText() - Method in class weka.classifiers.functions.LinearRegression
  Returns the tip text for this property
AttributeSelectionPanel - Class in weka.gui
  Creates a panel that displays the attributes contained in a set of instances, letting the user toggle whether each attribute is selected or not (eg: so that unselected attributes can be removed before classification).
AttributeSelectionPanel() - Constructor for class weka.gui.AttributeSelectionPanel
  Creates the attribute selection panel with no initial instances.
AttributeSelectionPanel - Class in weka.gui.explorer
  This panel allows the user to select and configure an attribute evaluator and a search method, set the attribute of the current dataset to be used as the class, and perform attribute selection using one of two selection modes (select using all the training data or perform a n-fold cross validation---on each trial selecting features using n-1 folds of the data).
AttributeSelectionPanel() - Constructor for class weka.gui.explorer.AttributeSelectionPanel
  Creates the classifier panel
attributeSparse(int) - Method in class weka.core.Instance
  Returns the attribute with the given index.
attributeSparse(int) - Method in class weka.core.SparseInstance
  Returns the attribute associated with the internal index.
AttributeStats - Class in weka.core
  A Utility class that contains summary information on an the values that appear in a dataset for a particular attribute.
AttributeStats() - Constructor for class weka.core.AttributeStats
attributeStats(int) - Method in class weka.core.Instances
  Calculates summary statistics on the values that appear in this set of instances for a specified attribute.
attributeString(Instances) - Method in class weka.classifiers.trees.adtree.Splitter
  Gets the string describing the attributes the split depends on.
attributeString(Instances) - Method in class weka.classifiers.trees.adtree.TwoWayNominalSplit
  Gets the string describing the attributes the split depends on.
attributeString(Instances) - Method in class weka.classifiers.trees.adtree.TwoWayNumericSplit
  Gets the string describing the attributes the split depends on.
AttributeSummarizer - Class in weka.gui.beans
  Bean that encapsulates displays bar graph summaries for attributes in a data set.
AttributeSummarizer() - Constructor for class weka.gui.beans.AttributeSummarizer
  Creates a new `AttributeSummarizer` instance.
AttributeSummarizerBeanInfo - Class in weka.gui.beans
  Bean info class for the attribute summarizer bean
AttributeSummarizerBeanInfo() - Constructor for class weka.gui.beans.AttributeSummarizerBeanInfo
AttributeSummaryPanel - Class in weka.gui
  This panel displays summary statistics about an attribute: name, type number/% of missing/unique values, number of distinct values.
AttributeSummaryPanel() - Constructor for class weka.gui.AttributeSummaryPanel
  Creates the instances panel with no initial instances.
attributeToDoubleArray(int) - Method in class weka.core.Instances
  Gets the value of all instances in this dataset for a particular attribute.
AttributeTransformer - Interface in weka.attributeSelection
  Abstract attribute transformer.
attributeTypeTipText() - Method in class weka.filters.unsupervised.attribute.RemoveType
  Returns the tip text for this property
AttributeValueLiteral - Class in weka.associations.tertius
AttributeValueLiteral(Predicate, String, int, int, int) - Constructor for class weka.associations.tertius.AttributeValueLiteral
AttributeVisualizationPanel - Class in weka.gui
  Creates a panel that shows a visualization of an attribute in a dataset.
AttributeVisualizationPanel() - Constructor for class weka.gui.AttributeVisualizationPanel
  Constructor - If used then the class will not show the class selection combo box.
AttributeVisualizationPanel(boolean) - Constructor for class weka.gui.AttributeVisualizationPanel
  Constructor.
attrSplit(int, Instances) - Method in class weka.classifiers.trees.m5.CorrelationSplitInfo
  Finds the best splitting point for an attribute in the instances
attrSplit(int, Instances) - Method in interface weka.classifiers.trees.m5.SplitEvaluate
  Finds the best splitting point for an attribute in the instances
attrSplit(int, Instances) - Method in class weka.classifiers.trees.m5.YongSplitInfo
  Finds the best splitting point for an attribute in the instances
attsToEliminatePerIterationTipText() - Method in class weka.attributeSelection.SVMAttributeEval
  Returns a tip text for this property suitable for display in the GUI
autoBuildTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
autoKeyGenerationTipText() - Method in class weka.core.converters.DatabaseSaver
  Returns the tip text fo this property
AveragingResultProducer - Class in weka.experiment
  AveragingResultProducer takes the results from a ResultProducer and submits the average to the result listener.
AveragingResultProducer() - Constructor for class weka.experiment.AveragingResultProducer
avgCost() - Method in class weka.classifiers.Evaluation
  Gets the average cost, that is, total cost of misclassifications (incorrect plus unclassified) over the total number of instances.
avgProb - Variable in class weka.classifiers.lazy.kstar.KStarWrapper
  used/reused to hold the average transformation probability

## B

B_ENTROPY - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
B_SPHERE - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
  Blend setting modes
backQuoteChars(String) - Static method in class weka.core.Utils
  Converts carriage returns and new lines in a string into \r and \n.
backward(PaceMatrix, IntVector, int, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Backward ordering of columns in terms of response explanation.
Bagging - Class in weka.classifiers.meta
  Class for bagging a classifier.
Bagging() - Constructor for class weka.classifiers.meta.Bagging
  Constructor.
bagSizePercentTipText() - Method in class weka.classifiers.meta.Bagging
  Returns the tip text for this property
bagSizePercentTipText() - Method in class weka.classifiers.meta.MetaCost
  Returns the tip text for this property
balancedTipText() - Method in class weka.classifiers.functions.Winnow
  Returns the tip text for this property
BATCH - Static variable in interface weka.core.converters.Saver
BATCH_FINISHED - Static variable in class weka.gui.beans.IncrementalClassifierEvent
BATCH_FINISHED - Static variable in class weka.gui.beans.InstanceEvent
BATCH_FINISHED - Static variable in class weka.gui.streams.InstanceEvent
  Specifies that the batch of instances is finished
BatchClassifierEvent - Class in weka.gui.beans
  Class encapsulating a built classifier and a batch of instances to test on.
BatchClassifierEvent(Object, Classifier, DataSetEvent, DataSetEvent, int, int) - Constructor for class weka.gui.beans.BatchClassifierEvent
  Creates a new `BatchClassifierEvent` instance.
BatchClassifierListener - Interface in weka.gui.beans
  Interface to something that can process a BatchClassifierEvent
BatchClustererEvent - Class in weka.gui.beans
  Class encapsulating a built clusterer and a batch of instances to test on.
BatchClustererEvent(Object, Clusterer, DataSetEvent, int, int, int) - Constructor for class weka.gui.beans.BatchClustererEvent
  Creates a new `BatchClustererEvent` instance.
BatchClustererListener - Interface in weka.gui.beans
  Interface to something that can process a BatchClustererEvent
BatchConverter - Interface in weka.core.converters
  Marker interface for a loader/saver that can retrieve instances in batch mode
batchFilterFile(Filter, String[]) - Static method in class weka.filters.Filter
  Method for testing filters ability to process multiple batches.
batchFinished() - Method in class weka.filters.Filter
  Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.attribute.AttributeSelection
  Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.attribute.ClassOrder
  Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.attribute.Discretize
  Signifies that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.attribute.NominalToBinary
  Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.instance.Resample
  Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.instance.SpreadSubsample
  Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds
  Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries
  Signifies that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.AddCluster
  Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.AddNoise
  Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.ClusterMembership
  Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.Discretize
  Signifies that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.Normalize
  Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.RandomProjection
  Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.RemoveType
  Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.RemoveUseless
  Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingValues
  Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.Standardize
  Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.StringToNominal
  Signifies that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.Randomize
  Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.RemoveFolds
  Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified
  Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.RemovePercentage
  Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.RemoveRange
  Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.Resample
  Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.gui.streams.InstanceJoiner
  Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.gui.streams.InstanceSavePanel
batchFinished() - Method in class weka.gui.streams.InstanceTable
batchFinished() - Method in class weka.gui.streams.InstanceViewer
BAYES - Static variable in interface weka.classifiers.bayes.net.search.local.Scoreable
  score types
BayesNet - Class in weka.classifiers.bayes
  Base class for a Bayes Network classifier.
BayesNet() - Constructor for class weka.classifiers.bayes.BayesNet
BayesNet - Static variable in interface weka.core.Drawable
BayesNetEstimator - Class in weka.classifiers.bayes.net.estimate
  BayesNetEstimator is the base class for estimating the conditional probability tables of a Bayes network once the structure has been learned.
BayesNetEstimator() - Constructor for class weka.classifiers.bayes.net.estimate.BayesNetEstimator
BayesNetGenerator - Class in weka.classifiers.bayes.net
  BayesNetGenerator offers facilities for generating random Bayes networks and random instances based on a Bayes network.
BayesNetGenerator() - Constructor for class weka.classifiers.bayes.net.BayesNetGenerator
  Constructor for BayesNetGenerator.
BDeu - Static variable in interface weka.classifiers.bayes.net.search.local.Scoreable
BEAN_EXECUTING - Static variable in class weka.gui.beans.BeanInstance
BeanCommon - Interface in weka.gui.beans
  Interface specifying routines that all weka beans should implement in order to allow the bean environment to exercise some control over the bean and also to allow the bean to excercise some control over connections.
BeanConnection - Class in weka.gui.beans
  Class for encapsulating a connection between two beans.
BeanConnection(BeanInstance, BeanInstance, EventSetDescriptor) - Constructor for class weka.gui.beans.BeanConnection
  Creates a new `BeanConnection` instance.
BeanInstance - Class in weka.gui.beans
  Class that manages a set of beans.
BeanInstance(JComponent, Object, int, int) - Constructor for class weka.gui.beans.BeanInstance
  Creates a new `BeanInstance` instance.
BeanInstance(JComponent, String, int, int) - Constructor for class weka.gui.beans.BeanInstance
  Creates a new `BeanInstance` instance given the fully qualified name of the bean
BeanVisual - Class in weka.gui.beans
  BeanVisual encapsulates icons and label for a given bean.
BeanVisual(String, String, String) - Constructor for class weka.gui.beans.BeanVisual
  Constructor
BestFirst - Class in weka.attributeSelection
  Class for performing a best first search.
BestFirst() - Constructor for class weka.attributeSelection.BestFirst
  Constructor
BestFirst.Link2 - Class in weka.attributeSelection
  Class for a node in a linked list.
BestFirst.Link2(Object[], double) - Constructor for class weka.attributeSelection.BestFirst.Link2
BestFirst.LinkedList2 - Class in weka.attributeSelection
  Class for handling a linked list.
BestFirst.LinkedList2(int) - Constructor for class weka.attributeSelection.BestFirst.LinkedList2
betaTipText() - Method in class weka.classifiers.functions.Winnow
  Returns the tip text for this property
bias() - Method in class weka.classifiers.functions.SMO
  Returns the bias of each binary SMO.
biasTipText() - Method in class weka.classifiers.misc.VFI
  Returns the tip text for this property
biasToUniformClassTipText() - Method in class weka.filters.supervised.instance.Resample
  Returns the tip text for this property
BIFFileTipText() - Method in class weka.classifiers.bayes.BayesNet
BIFFormatException - Exception in weka.gui.graphvisualizer
  This is the Exception thrown by BIFParser, if there was an error in parsing the XMLBIF string or input stream.
BIFFormatException(String) - Constructor for exception weka.gui.graphvisualizer.BIFFormatException
BIFParser - Class in weka.gui.graphvisualizer
  This class parses an inputstream or a string in XMLBIF ver.
BIFParser(String, FastVector, FastVector) - Constructor for class weka.gui.graphvisualizer.BIFParser
  Constructor (if our input is a String)
BIFParser(InputStream, FastVector, FastVector) - Constructor for class weka.gui.graphvisualizer.BIFParser
  Constructor (if our input is an InputStream)
BIFReader - Class in weka.classifiers.bayes.net
  Builds a description of a Bayes Net classifier stored in XML BIF 0.3 format.
BIFReader() - Constructor for class weka.classifiers.bayes.net.BIFReader
binarizeNumericAttributesTipText() - Method in class weka.attributeSelection.ChiSquaredAttributeEval
  Returns the tip text for this property
binarizeNumericAttributesTipText() - Method in class weka.attributeSelection.InfoGainAttributeEval
  Returns the tip text for this property
binaryAttributesNominalTipText() - Method in class weka.filters.supervised.attribute.NominalToBinary
  Returns the tip text for this property
binaryAttributesNominalTipText() - Method in class weka.filters.unsupervised.attribute.NominalToBinary
  Returns the tip text for this property
BinarySparseInstance - Class in weka.core
  Class for storing a binary-data-only instance as a sparse vector.
BinarySparseInstance(Instance) - Constructor for class weka.core.BinarySparseInstance
  Constructor that generates a sparse instance from the given instance.
BinarySparseInstance(SparseInstance) - Constructor for class weka.core.BinarySparseInstance
  Constructor that copies the info from the given instance.
BinarySparseInstance(double, double[]) - Constructor for class weka.core.BinarySparseInstance
  Constructor that generates a sparse instance from the given parameters.
BinarySparseInstance(double, int[], int) - Constructor for class weka.core.BinarySparseInstance
  Constructor that inititalizes instance variable with given values.
BinarySparseInstance(int) - Constructor for class weka.core.BinarySparseInstance
  Constructor of an instance that sets weight to one, all values to 1, and the reference to the dataset to null.
binarySplitsTipText() - Method in class weka.classifiers.rules.PART
  Returns the tip text for this property
binarySplitsTipText() - Method in class weka.classifiers.trees.J48
  Returns the tip text for this property
binaryToKOML(String, String) - Static method in class weka.core.xml.SerialUIDChanger
  converts a binary file into a KOML XML file
BinC45ModelSelection - Class in weka.classifiers.trees.j48
  Class for selecting a C4.5-like binary (!) split for a given dataset.
BinC45ModelSelection(int, Instances) - Constructor for class weka.classifiers.trees.j48.BinC45ModelSelection
  Initializes the split selection method with the given parameters.
BinC45Split - Class in weka.classifiers.trees.j48
  Class implementing a binary C4.5-like split on an attribute.
BinC45Split(int, int, double) - Constructor for class weka.classifiers.trees.j48.BinC45Split
  Initializes the split model.
binomialDistribution(double, double, double) - Static method in class weka.associations.RuleGeneration
  calculates the probability using a binomial distribution.
binomialStandardError(double, int) - Static method in class weka.core.Statistics
  Computes standard error for observed values of a binomial random variable.
binomP(double, double, double) - Method in class weka.classifiers.lazy.LBR
  Significance test binomp:
binsTipText() - Method in class weka.filters.unsupervised.attribute.Discretize
  Returns the tip text for this property
binsTipText() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize
  Returns the tip text for this property
BIRCHCluster - Class in weka.datagenerators
  Cluster data generator designed for the BIRCH System Dataset is generated with instances in K clusters.
BIRCHCluster() - Constructor for class weka.datagenerators.BIRCHCluster
blocker(boolean) - Method in class weka.classifiers.functions.MultilayerPerceptron
  A function used to stop the code that called buildclassifier from continuing on before the user has finished the decision tree.
BMAEstimator - Class in weka.classifiers.bayes.net.estimate
  BMAEstimator estimates conditional probability tables of a Bayes network using Bayes Model Averaging (BMA).
BMAEstimator() - Constructor for class weka.classifiers.bayes.net.estimate.BMAEstimator
Body - Class in weka.associations.tertius
  Class representing the body of a rule.
Body() - Constructor for class weka.associations.tertius.Body
  Constructor without storing the counter-instances.
Body(Instances) - Constructor for class weka.associations.tertius.Body
  Constructor storing the counter-instances.
bodyContains(Literal) - Method in class weka.associations.tertius.Rule
  Test if the body of the rule contains a literal.
BOOL - Static variable in class weka.core.converters.DatabaseLoader
BOOL - Static variable in class weka.experiment.DatabaseUtils
  Type mapping for BOOL used for reading experiment results
boost() - Method in class weka.classifiers.trees.ADTree
  Performs a single boosting iteration, using two-class optimized method.
BoundaryPanel - Class in weka.gui.boundaryvisualizer
  BoundaryPanel.
BoundaryPanel(int, int) - Constructor for class weka.gui.boundaryvisualizer.BoundaryPanel
  Creates a new `BoundaryPanel` instance.
BoundaryPanelDistributed - Class in weka.gui.boundaryvisualizer
  This class extends BoundaryPanel with code for distributing the processing necessary to create a visualization among a list of remote machines.
BoundaryPanelDistributed(int, int) - Constructor for class weka.gui.boundaryvisualizer.BoundaryPanelDistributed
  Creates a new `BoundaryPanelDistributed` instance.
BoundaryVisualizer - Class in weka.gui.boundaryvisualizer
  BoundaryVisualizer.
BoundaryVisualizer() - Constructor for class weka.gui.boundaryvisualizer.BoundaryVisualizer
  Creates a new `BoundaryVisualizer` instance.
branchInstanceGoesDown(Instance) - Method in class weka.classifiers.trees.adtree.Splitter
  Gets the index of the branch that an instance applies to.
branchInstanceGoesDown(Instance) - Method in class weka.classifiers.trees.adtree.TwoWayNominalSplit
  Gets the index of the branch that an instance applies to.
branchInstanceGoesDown(Instance) - Method in class weka.classifiers.trees.adtree.TwoWayNumericSplit
  Gets the index of the branch that an instance applies to.
build(String, String) - Method in class weka.gui.HierarchyPropertyParser
  Build a tree from the given property with the given delimitor
buildAssociations(Instances) - Method in class weka.associations.Apriori
  Method that generates all large itemsets with a minimum support, and from these all association rules with a minimum confidence.
buildAssociations(Instances) - Method in class weka.associations.Associator
  Generates an associator.
buildAssociations(Instances) - Method in class weka.associations.PredictiveApriori
  Method that generates all large itemsets with a minimum support, and from these all association rules.
buildAssociations(Instances) - Method in class weka.associations.Tertius
  Method that launches the search to find the rules with the highest confirmation.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.AODE
  Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.BayesNet
  Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.ComplementNaiveBayes
  Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.NaiveBayes
  Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.NaiveBayesMultinomial
  Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.NaiveBayesSimple
  Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.Classifier
  Generates a classifier.
buildClassifier(Instances) - Method in class weka.classifiers.functions.LeastMedSq
  Build lms regression
buildClassifier(Instances) - Method in class weka.classifiers.functions.LinearRegression
  Builds a regression model for the given data.
buildClassifier(Instances) - Method in class weka.classifiers.functions.Logistic
  Builds the classifier
buildClassifier(Instances) - Method in class weka.classifiers.functions.MultilayerPerceptron
  Call this function to build and train a neural network for the training data provided.
buildClassifier(Instances) - Method in class weka.classifiers.functions.PaceRegression
  Builds a pace regression model for the given data.
buildClassifier(Instances) - Method in class weka.classifiers.functions.RBFNetwork
  Builds the classifier
buildClassifier(Instances) - Method in class weka.classifiers.functions.SimpleLinearRegression
  Builds a simple linear regression model given the supplied training data.
buildClassifier(Instances) - Method in class weka.classifiers.functions.SimpleLogistic
  Builds the logistic regression using LogitBoost.
buildClassifier(Instances) - Method in class weka.classifiers.functions.SMO
  Method for building the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.functions.SMOreg
  Method for building the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.functions.VotedPerceptron
  Builds the ensemble of perceptrons.
buildClassifier(Instances) - Method in class weka.classifiers.functions.Winnow
  Builds the classifier
buildClassifier(Instances) - Method in class weka.classifiers.IteratedSingleClassifierEnhancer
  Stump method for building the classifiers.
buildClassifier(Instances) - Method in class weka.classifiers.lazy.IB1
  Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.lazy.IBk
  Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.lazy.KStar
  Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.lazy.LBR
  For lazy learning, building classifier is only to prepare their inputs until classification time.
buildClassifier(Instances) - Method in class weka.classifiers.lazy.LWL
  Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.AdaBoostM1
  Boosting method.
buildClassifier(Instances) - Method in class weka.classifiers.meta.AdditiveRegression
  Build the classifier on the supplied data
buildClassifier(Instances) - Method in class weka.classifiers.meta.AttributeSelectedClassifier
  Build the classifier on the dimensionally reduced data.
buildClassifier(Instances) - Method in class weka.classifiers.meta.Bagging
  Bagging method.
buildClassifier(Instances) - Method in class weka.classifiers.meta.ClassificationViaRegression
  Builds the classifiers.
buildClassifier(Instances) - Method in class weka.classifiers.meta.CostSensitiveClassifier
  Builds the model of the base learner.
buildClassifier(Instances) - Method in class weka.classifiers.meta.CVParameterSelection
  Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.Decorate
  Build Decorate classifier
buildClassifier(Instances) - Method in class weka.classifiers.meta.FilteredClassifier
  Build the classifier on the filtered data.
buildClassifier(Instances) - Method in class weka.classifiers.meta.LogitBoost
  Builds the boosted classifier
buildClassifier(Instances) - Method in class weka.classifiers.meta.MetaCost
  Builds the model of the base learner.
buildClassifier(Instances) - Method in class weka.classifiers.meta.MultiBoostAB
  Method for building this classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.MultiClassClassifier
  Builds the classifiers.
buildClassifier(Instances) - Method in class weka.classifiers.meta.MultiScheme
  Buildclassifier selects a classifier from the set of classifiers by minimising error on the training data.
buildClassifier(Instances) - Method in class weka.classifiers.meta.OrdinalClassClassifier
  Builds the classifiers.
buildClassifier(Instances) - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost
  Builds the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.RandomCommittee
  Builds the committee of randomizable classifiers.
buildClassifier(Instances) - Method in class weka.classifiers.meta.RegressionByDiscretization
  Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.Stacking
  Buildclassifier selects a classifier from the set of classifiers by minimising error on the training data.
buildClassifier(Instances) - Method in class weka.classifiers.meta.ThresholdSelector
  Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.Vote
  Buildclassifier selects a classifier from the set of classifiers by minimising error on the training data.
buildClassifier(Instances) - Method in class weka.classifiers.misc.HyperPipes
  Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.misc.VFI
  Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.rules.ConjunctiveRule
  Builds a single rule learner with REP dealing with nominal classes or numeric classes.
buildClassifier(Instances) - Method in class weka.classifiers.rules.DecisionTable
  Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.rules.JRip
  Builds Ripper in the order of class frequencies.
buildClassifier(Instances) - Method in class weka.classifiers.rules.NNge
  Generates a classifier.
buildClassifier(Instances) - Method in class weka.classifiers.rules.OneR
  Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.rules.PART
  Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.rules.part.MakeDecList
  Builds dec list.
buildClassifier(Instances) - Method in class weka.classifiers.rules.Prism
  Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.rules.Ridor
  Builds a ripple-down manner rule learner.
buildClassifier(Instances) - Method in class weka.classifiers.rules.ZeroR
  Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.ADTree
  Builds a classifier for a set of instances.
buildClassifier(Instances) - Method in class weka.classifiers.trees.DecisionStump
  Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.Id3
  Builds Id3 decision tree classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.BinC45Split
  Creates a C4.5-type split on the given data.
buildClassifier(Instances) - Method in class weka.classifiers.trees.J48
  Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.C45PruneableClassifierTree
  Method for building a pruneable classifier tree.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.C45Split
  Creates a C4.5-type split on the given data.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
  Builds the classifier split model for the given set of instances.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.ClassifierTree
  Method for building a classifier tree.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.NBTreeClassifierTree
  Method for building a naive bayes classifier tree
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.NBTreeNoSplit
  Build the no-split node
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.NBTreeSplit
  Creates a NBTree-type split on the given data.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.NoSplit
  Creates a "no-split"-split for a given set of instances.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.PruneableClassifierTree
  Method for building a pruneable classifier tree.
buildClassifier(Instances) - Method in class weka.classifiers.trees.LMT
  Builds the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.lmt.LMTNode
  Method for building a logistic model tree (only called for the root node).
buildClassifier(Instances) - Method in class weka.classifiers.trees.lmt.LogisticBase
  Builds the logistic regression model usiing LogitBoost.
buildClassifier(Instances, double[][], double[][]) - Method in class weka.classifiers.trees.lmt.ResidualSplit
  Builds the split.
buildClassifier(Instances) - Method in class weka.classifiers.trees.lmt.ResidualSplit
  Method not in use
buildClassifier(Instances) - Method in class weka.classifiers.trees.m5.M5Base
  Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.m5.PreConstructedLinearModel
  Builds the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.m5.Rule
  Generates a single rule or m5 model tree.
buildClassifier(Instances) - Method in class weka.classifiers.trees.m5.RuleNode
  Build this node (find an attribute and split point)
buildClassifier(Instances) - Method in class weka.classifiers.trees.NBTree
  Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.RandomForest
  Builds a classifier for a set of instances.
buildClassifier(Instances) - Method in class weka.classifiers.trees.RandomTree
  Builds classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.REPTree
  Builds classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.UserClassifier
  Call this function to build a decision tree for the training data provided.
buildClusterer(Instances) - Method in class weka.clusterers.Clusterer
  Generates a clusterer.
buildClusterer(Instances) - Method in class weka.clusterers.Cobweb
  Builds the clusterer.
buildClusterer(Instances) - Method in class weka.clusterers.EM
  Generates a clusterer.
buildClusterer(Instances) - Method in class weka.clusterers.FarthestFirst
  Generates a clusterer.
buildClusterer(Instances) - Method in class weka.clusterers.MakeDensityBasedClusterer
  Builds a clusterer for a set of instances.
buildClusterer(Instances) - Method in class weka.clusterers.SimpleKMeans
  Generates a clusterer.
buildDecList(Instances, boolean) - Method in class weka.classifiers.rules.part.C45PruneableDecList
  Builds the partial tree without hold out set.
buildDecList(Instances, boolean) - Method in class weka.classifiers.rules.part.ClassifierDecList
  Builds the partial tree without hold out set.
buildDecList(Instances, Instances, boolean) - Method in class weka.classifiers.rules.part.PruneableDecList
  Builds the partial tree with hold out set
buildDistribution(double, double) - Method in class weka.associations.PriorEstimation
  updates the distribution of the confidence values.
buildEvaluator(Instances) - Method in class weka.attributeSelection.ASEvaluation
  Generates a attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.CfsSubsetEval
  Generates a attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.ChiSquaredAttributeEval
  Initializes a chi-squared attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.ClassifierSubsetEval
  Generates a attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.ConsistencySubsetEval
  Generates a attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.GainRatioAttributeEval
  Initializes a gain ratio attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.InfoGainAttributeEval
  Initializes an information gain attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.OneRAttributeEval
  Initializes a OneRAttribute attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.PrincipalComponents
  Initializes principal components and performs the analysis
buildEvaluator(Instances) - Method in class weka.attributeSelection.ReliefFAttributeEval
  Initializes a ReliefF attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.SVMAttributeEval
  Initializes the evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval
  Initializes a symmetrical uncertainty attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.WrapperSubsetEval
  Generates a attribute evaluator.
buildGenerator(Instances) - Method in interface weka.gui.boundaryvisualizer.DataGenerator
  Build the data generator
buildGenerator(Instances) - Method in class weka.gui.boundaryvisualizer.KDDataGenerator
  Initialize the generator using the supplied instances
buildLogisticModelsTipText() - Method in class weka.classifiers.functions.SMO
  Returns the tip text for this property
buildRule(Instances) - Method in class weka.classifiers.rules.part.ClassifierDecList
  Method for building a pruned partial tree.
buildRule(Instances, Instances) - Method in class weka.classifiers.rules.part.PruneableDecList
  Method for building a pruned partial tree.
buildStructure() - Method in class weka.classifiers.bayes.BayesNet
  buildStructure determines the network structure/graph of the network.
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.fixed.FromFile
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.fixed.NaiveBayes
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.global.K2
  buildStructure determines the network structure/graph of the network with the K2 algorithm, restricted by its initial structure (which can be an empty graph, or a Naive Bayes graph.
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.global.TAN
  buildStructure determines the network structure/graph of the network using the maximimum weight spanning tree algorithm of Chow and Liu
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.local.K2
  buildStructure determines the network structure/graph of the network with the K2 algorithm, restricted by its initial structure (which can be an empty graph, or a Naive Bayes graph.
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
  buildStructure determines the network structure/graph of the network with the K2 algorithm, restricted by its initial structure (which can be an empty graph, or a Naive Bayes graph.
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.local.TAN
  buildStructure determines the network structure/graph of the network using the maximimum weight spanning tree algorithm of Chow and Liu
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.SearchAlgorithm
  buildStructure determines the network structure/graph of the network.
buildTree(Instances, boolean) - Method in class weka.classifiers.trees.j48.ClassifierTree
  Builds the tree structure.
buildTree(Instances, Instances, boolean) - Method in class weka.classifiers.trees.j48.ClassifierTree
  Builds the tree structure with hold out set
buildTree(Instances, SimpleLinearRegression[][], double) - Method in class weka.classifiers.trees.lmt.LMTNode
  Method for building the tree structure.
BVDecompose - Class in weka.classifiers
  Class for performing a Bias-Variance decomposition on any classifier using the method specified in:
BVDecompose() - Constructor for class weka.classifiers.BVDecompose
BVDecomposeSegCVSub - Class in weka.classifiers
  This class performs Bias-Variance decomposion on any classifier using the sub-sampled cross-validation procedure as specified in:
BVDecomposeSegCVSub() - Constructor for class weka.classifiers.BVDecomposeSegCVSub
BYTE - Static variable in class weka.core.converters.DatabaseLoader
BYTE - Static variable in class weka.experiment.DatabaseUtils
  Type mapping for BYTE used for reading experiment results

## C

C45Loader - Class in weka.core.converters
  Reads C4.5 input files.
C45Loader() - Constructor for class weka.core.converters.C45Loader
C45ModelSelection - Class in weka.classifiers.trees.j48
  Class for selecting a C4.5-type split for a given dataset.
C45ModelSelection(int, Instances) - Constructor for class weka.classifiers.trees.j48.C45ModelSelection
  Initializes the split selection method with the given parameters.
C45PruneableClassifierTree - Class in weka.classifiers.trees.j48
  Class for handling a tree structure that can be pruned using C4.5 procedures.
C45PruneableClassifierTree(ModelSelection, boolean, float, boolean, boolean) - Constructor for class weka.classifiers.trees.j48.C45PruneableClassifierTree
  Constructor for pruneable tree structure.
C45PruneableDecList - Class in weka.classifiers.rules.part
  Class for handling a partial tree structure pruned using C4.5's pruning heuristic.
C45PruneableDecList(ModelSelection, double, int) - Constructor for class weka.classifiers.rules.part.C45PruneableDecList
  Constructor for pruneable tree structure.
C45Saver - Class in weka.core.converters
  Writes to a destination in the format used by the C4.5 slgorithm.
C45Saver() - Constructor for class weka.core.converters.C45Saver
  Constructor
C45Split - Class in weka.classifiers.trees.j48
  Class implementing a C4.5-type split on an attribute.
C45Split(int, int, double) - Constructor for class weka.classifiers.trees.j48.C45Split
  Initializes the split model.
CachedKernel - Class in weka.classifiers.functions.supportVector
  Base class for RBFKernel and PolyKernel that implements a simple LRU.
cacheKeyNameTipText() - Method in class weka.experiment.DatabaseResultListener
  Returns the tip text for this property
cacheSizeTipText() - Method in class weka.classifiers.functions.SMO
  Returns the tip text for this property
cacheSizeTipText() - Method in class weka.classifiers.functions.SMOreg
  Returns the tip text for this property
calcColumnWidth(int) - Method in class weka.gui.JTableHelper
  calcs the optimal column width of the given column
calcColumnWidth(JTable, int) - Static method in class weka.gui.JTableHelper
  Calculates the optimal width for the column of the given table.
calcGraph() - Method in class weka.gui.AttributeVisualizationPanel
  Recalculates the barplot or histogram to display, required usually when the attribute is changed or the component is resized.
calcHeaderWidth(int) - Method in class weka.gui.JTableHelper
  calcs the optimal header width of the given column
calcHeaderWidth(JTable, int) - Static method in class weka.gui.JTableHelper
  Calculates the optimal width for the header of the given table.
calcNodeScore(int) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
  Calc Node Score for given parent set
calcOutOfBagTipText() - Method in class weka.classifiers.meta.Bagging
  Returns the tip text for this property
calcScore(BayesNet) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
  performCV returns the accuracy calculated using cross validation.
calcScoreWithExtraParent(int, int) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
  Calc Node Score With Added Parent
calcScoreWithExtraParent(int, int) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
  Calc Node Score With AddedParent
calcScoreWithMissingParent(int, int) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
  Calc Node Score With Parent Deleted
calcScoreWithMissingParent(int, int) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
  Calc Node Score With Parent Deleted
calcScoreWithReversedParent(int, int) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
  Calc Node Score With Arrow reversed
calculateAlphas() - Method in class weka.classifiers.trees.lmt.LMTNode
  Updates the alpha field for all nodes.
calculateConfirmation() - Method in class weka.associations.tertius.Rule
  Calculate the confirmation of this rule.
calculateDerived() - Method in class weka.experiment.PairedStats
  Calculates the derived statistics (significance etc).
calculateDerived() - Method in class weka.experiment.PairedStatsCorrected
  Calculates the derived statistics (significance etc).
calculateDerived() - Method in class weka.experiment.Stats
  Tells the object to calculate any statistics that don't have their values automatically updated during add.
calculateOptimistic() - Method in class weka.associations.tertius.Rule
  Calculate the optimistic estimate of this rule.
calculatePriorSum(boolean, double) - Method in class weka.associations.PriorEstimation
  calculates the numerator and the denominator of the prior equation
calculateStatistics(Instance, int, int, int) - Method in class weka.experiment.PairedCorrectedTTester
  Computes a paired t-test comparison for a specified dataset between two resultsets.
calculateStatistics(Instance, int, int, int) - Method in class weka.experiment.PairedTTester
  Computes a paired t-test comparison for a specified dataset between two resultsets.
calculateStdDevsTipText() - Method in class weka.experiment.AveragingResultProducer
  Returns the tip text for this property
canAcceptConnection(Class) - Method in class weka.gui.beans.MetaBean
  Checks to see if any of the inputs to this group implements the supplied listener class
cancel() - Method in class weka.core.converters.AbstractFileSaver
  Cancels the incremental saving process.
cancel() - Method in class weka.core.converters.AbstractSaver
  Cancels the incremental saving process if the write mode is CANCEL.
cancel() - Method in class weka.core.converters.DatabaseSaver
  Cancels the incremental saving process and tries to drop the table if the write mode is CANCEL.
CANCEL_OPTION - Static variable in class weka.gui.experiment.OutputFormatDialog
  Signifies a cancelled property selection
CANCEL_OPTION - Static variable in class weka.gui.ListSelectorDialog
  Signifies a cancelled property selection
CANCEL_OPTION - Static variable in class weka.gui.PropertySelectorDialog
  Signifies a cancelled property selection
CANCEL_OPTION - Static variable in class weka.gui.ViewerDialog
  Signifies a cancelled property selection
canKeep(Instance, Literal) - Method in class weka.associations.tertius.Body
  Test if an instance can be kept as a counter-instance, if a new literal is added to this body.
canKeep(Instance, Literal) - Method in class weka.associations.tertius.Head
  Test if an instance can be kept as a counter-instance, if a new literal is added to this head.
canKeep(Instance, Literal) - Method in class weka.associations.tertius.LiteralSet
  Test if an instance can be kept as a counter-instance, given a new literal.
canUndo() - Method in interface weka.core.Undoable
  returns whether an undo is possible, i.e.
canUndo() - Method in class weka.gui.arffviewer.ArffPanel
  returns whether an undo is possible
canUndo() - Method in class weka.gui.arffviewer.ArffTableModel
  returns whether an undo is possible, i.e.
canUndo() - Method in class weka.gui.arffviewer.ArffTableSorter
  returns whether an undo is possible, i.e.
capacity() - Method in class weka.classifiers.functions.pace.DoubleVector
  Gets the capacity of the vector.
capacity() - Method in class weka.classifiers.functions.pace.IntVector
  Returns the capacity of the vector
capacity() - Method in class weka.core.FastVector
  Returns the capacity of the vector.
cat(DoubleVector) - Method in class weka.classifiers.functions.pace.DoubleVector
  Combine two vectors together
cbind(PaceMatrix) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Returns a new matrix which binds two matrices with columns.
CfsSubsetEval - Class in weka.attributeSelection
  CFS attribute subset evaluator.
CfsSubsetEval() - Constructor for class weka.attributeSelection.CfsSubsetEval
  Constructor
change() - Method in class weka.associations.RuleGeneration
  Gets if the list fo the best rules has been changed
ChangeDateFormat - Class in weka.filters.unsupervised.attribute
  Changes the date format used by a date attribute.
ChangeDateFormat() - Constructor for class weka.filters.unsupervised.attribute.ChangeDateFormat
changeUID(long, long, String, String) - Static method in class weka.core.xml.SerialUIDChanger
  changes the oldUID into newUID from the given file (binary/KOML) into the other one (binary/KOML).
ChartEvent - Class in weka.gui.beans
  Event encapsulating info for plotting a data point on the StripChart
ChartEvent(Object, Vector, double, double, double[], boolean) - Constructor for class weka.gui.beans.ChartEvent
  Creates a new `ChartEvent` instance.
ChartEvent(Object) - Constructor for class weka.gui.beans.ChartEvent
  Creates a new `ChartEvent` instance.
ChartListener - Interface in weka.gui.beans
  Interface to something that can process a ChartEvent
check(double) - Method in class weka.classifiers.trees.j48.Distribution
  Checks if at least two bags contain a minimum number of instances.
CheckClassifier - Class in weka.classifiers
  Class for examining the capabilities and finding problems with classifiers.
CheckClassifier() - Constructor for class weka.classifiers.CheckClassifier
CheckClassifier.PostProcessor - Class in weka.classifiers
  a class for postprocessing the test-data
CheckClassifier.PostProcessor() - Constructor for class weka.classifiers.CheckClassifier.PostProcessor
checkErrorRateTipText() - Method in class weka.classifiers.rules.JRip
  Returns the tip text for this property
checkForMissing(Instances) - Method in class weka.classifiers.functions.PaceRegression
  Checks if instances have a missing value.
checkForMissing(Instance, Instances) - Method in class weka.classifiers.functions.PaceRegression
  Checks if an instance has a missing value.
checkForNonBinary(Instances) - Method in class weka.classifiers.functions.PaceRegression
  Checks if any of the nominal attributes is non-binary.
checkForRemainingOptions(String[]) - Static method in class weka.core.Utils
  Checks if the given array contains any non-empty options.
checkForStringAttributes() - Method in class weka.core.Instances
  Checks for string attributes in the dataset
checkInstance(Instance) - Method in class weka.core.Instances
  Checks if the given instance is compatible with this dataset.
checkModel() - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
  Checks if generated model is valid.
checkModel(int) - Method in class weka.classifiers.trees.lmt.ResidualSplit
  Checks if there are at least 2 subsets that contain >= minNumInstances.
checkModel() - Method in class weka.gui.TableSorter
CheckOptionHandler - Class in weka.core
  Simple command line checking of classes that implement OptionHandler.
CheckOptionHandler() - Constructor for class weka.core.CheckOptionHandler
checkOptionHandler(OptionHandler, String[]) - Static method in class weka.core.CheckOptionHandler
  Runs some diagnostic tests on an optionhandler object.
checkStatus(Object) - Method in interface weka.experiment.Compute
  Check on the status of a `Task`
checkStatus(Object) - Method in class weka.experiment.RemoteEngine
  Returns status information on a particular task
children() - Method in class weka.classifiers.trees.adtree.PredictionNode
  Enumerates the children of this node.
childrenValues() - Method in class weka.gui.HierarchyPropertyParser
  The value in the children nodes.
chisqDistribution - Static variable in class weka.classifiers.functions.pace.Maths
  Distribution type: chi-squared
ChisqMixture - Class in weka.classifiers.functions.pace
  Class for manipulating chi-square mixture distributions.
ChisqMixture() - Constructor for class weka.classifiers.functions.pace.ChisqMixture
  Contructs an empty ChisqMixture
chiSquared(double[][], boolean) - Static method in class weka.core.ContingencyTables
  Returns chi-squared probability for a given matrix.
ChiSquaredAttributeEval - Class in weka.attributeSelection
  Class for Evaluating attributes individually by measuring the chi-squared statistic with respect to the class.
ChiSquaredAttributeEval() - Constructor for class weka.attributeSelection.ChiSquaredAttributeEval
  Constructor
chiSquaredProbability(double, double) - Static method in class weka.core.Statistics
  Returns chi-squared probability for given value and degrees of freedom.
chiVal(double[][], boolean) - Static method in class weka.core.ContingencyTables
  Computes chi-squared statistic for a contingency table.
chol() - Method in class weka.core.matrix.Matrix
  Cholesky Decomposition
CholeskyDecomposition - Class in weka.core.matrix
  Cholesky Decomposition.
CholeskyDecomposition(Matrix) - Constructor for class weka.core.matrix.CholeskyDecomposition
  Cholesky algorithm for symmetric and positive definite matrix.
chooseIndex() - Method in class weka.classifiers.rules.part.ClassifierDecList
  Method for choosing a subset to expand.
chooseLastIndex() - Method in class weka.classifiers.rules.part.ClassifierDecList
  Choose last index (ie.
CISearchAlgorithm - Class in weka.classifiers.bayes.net.search.ci
  The CISearchAlgorithm class supports Bayes net structure search algorithms that are based on conditional independence test (as opposed to for example score based of cross validation based search algorithms).
CISearchAlgorithm() - Constructor for class weka.classifiers.bayes.net.search.ci.CISearchAlgorithm
ClassAssigner - Class in weka.gui.beans
  Bean that assigns a class attribute to a data set.
ClassAssigner() - Constructor for class weka.gui.beans.ClassAssigner
ClassAssignerBeanInfo - Class in weka.gui.beans
  BeanInfo class for the class assigner bean
ClassAssignerBeanInfo() - Constructor for class weka.gui.beans.ClassAssignerBeanInfo
ClassAssignerCustomizer - Class in weka.gui.beans
  GUI customizer for the class assigner bean
ClassAssignerCustomizer() - Constructor for class weka.gui.beans.ClassAssignerCustomizer
classAttribute() - Method in class weka.core.Instance
  Returns class attribute.
classAttribute() - Method in class weka.core.Instances
  Returns the class attribute.
classAttributeNames() - Method in class weka.classifiers.functions.SMO
classColumnTipText() - Method in class weka.gui.beans.ClassAssigner
  Tool tip text for this property
classFirst(boolean) - Method in class weka.experiment.Experiment
  Sets whether the first attribute is treated as the class for all datasets involved in the experiment.
classificationTipText() - Method in class weka.associations.Tertius
  Returns the tip text for this property.
ClassificationViaRegression - Class in weka.classifiers.meta
  Class for doing classification using regression methods.
ClassificationViaRegression() - Constructor for class weka.classifiers.meta.ClassificationViaRegression
  Default constructor.
Classifier - Class in weka.classifiers
  Abstract classifier.
Classifier() - Constructor for class weka.classifiers.Classifier
Classifier - Class in weka.gui.beans
  Bean that wraps around weka.classifiers
Classifier() - Constructor for class weka.gui.beans.Classifier
  Creates a new `Classifier` instance.
ClassifierBeanInfo - Class in weka.gui.beans
  BeanInfo class for the Classifier wrapper bean
ClassifierBeanInfo() - Constructor for class weka.gui.beans.ClassifierBeanInfo
ClassifierCustomizer - Class in weka.gui.beans
  GUI customizer for the classifier wrapper bean
ClassifierCustomizer() - Constructor for class weka.gui.beans.ClassifierCustomizer
ClassifierDecList - Class in weka.classifiers.rules.part
  Class for handling a rule (partial tree) for a decision list.
ClassifierDecList(ModelSelection, int) - Constructor for class weka.classifiers.rules.part.ClassifierDecList
  Constructor - just calls constructor of class DecList.
ClassifierPanel - Class in weka.gui.explorer
  This panel allows the user to select and configure a classifier, set the attribute of the current dataset to be used as the class, and evaluate the classifier using a number of testing modes (test on the training data, train/test on a percentage split, n-fold cross-validation, test on a separate split).
ClassifierPanel() - Constructor for class weka.gui.explorer.ClassifierPanel
  Creates the classifier panel
ClassifierPerformanceEvaluator - Class in weka.gui.beans
  A bean that evaluates the performance of batch trained classifiers
ClassifierPerformanceEvaluator() - Constructor for class weka.gui.beans.ClassifierPerformanceEvaluator
ClassifierPerformanceEvaluatorBeanInfo - Class in weka.gui.beans
  Bean info class for the classifier performance evaluator
ClassifierPerformanceEvaluatorBeanInfo() - Constructor for class weka.gui.beans.ClassifierPerformanceEvaluatorBeanInfo
classifiers() - Method in class weka.classifiers.meta.LogitBoost
  Returns the array of classifiers that have been built.
ClassifierSplitEvaluator - Class in weka.experiment
  A SplitEvaluator that produces results for a classification scheme on a nominal class attribute.
ClassifierSplitEvaluator() - Constructor for class weka.experiment.ClassifierSplitEvaluator
  No args constructor.
ClassifierSplitModel - Class in weka.classifiers.trees.j48
  Abstract class for classification models that can be used recursively to split the data.
ClassifierSplitModel() - Constructor for class weka.classifiers.trees.j48.ClassifierSplitModel
classifiersTipText() - Method in class weka.classifiers.meta.MultiScheme
  Returns the tip text for this property
classifiersTipText() - Method in class weka.classifiers.MultipleClassifiersCombiner
  Returns the tip text for this property
ClassifierSubsetEval - Class in weka.attributeSelection
  Classifier subset evaluator.
ClassifierSubsetEval() - Constructor for class weka.attributeSelection.ClassifierSubsetEval
classifierTipText() - Method in class weka.attributeSelection.ClassifierSubsetEval
  Returns the tip text for this property
classifierTipText() - Method in class weka.attributeSelection.WrapperSubsetEval
  Returns the tip text for this property
classifierTipText() - Method in class weka.classifiers.SingleClassifierEnhancer
  Returns the tip text for this property
classifierTipText() - Method in class weka.experiment.ClassifierSplitEvaluator
  Returns the tip text for this property
classifierTipText() - Method in class weka.experiment.RegressionSplitEvaluator
  Returns the tip text for this property
classifierTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified
  Returns the tip text for this property
ClassifierTree - Class in weka.classifiers.trees.j48
  Class for handling a tree structure used for classification.
ClassifierTree(ModelSelection) - Constructor for class weka.classifiers.trees.j48.ClassifierTree
  Constructor.
CLASSIFY_CHILD - Static variable in class weka.gui.treevisualizer.TreeDisplayEvent
  Asks for another learning scheme to classify this node.
classifyInstance(Instance) - Method in class weka.classifiers.bayes.ComplementNaiveBayes
  Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.Classifier
  Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.functions.LeastMedSq
  Classify a given instance using the best generated LinearRegression Classifier.
classifyInstance(Instance) - Method in class weka.classifiers.functions.LinearRegression
  Classifies the given instance using the linear regression function.
classifyInstance(Instance) - Method in class weka.classifiers.functions.PaceRegression
  Classifies the given instance using the linear regression function.
classifyInstance(Instance) - Method in class weka.classifiers.functions.SimpleLinearRegression
  Generate a prediction for the supplied instance.
classifyInstance(Instance) - Method in class weka.classifiers.functions.SMOreg
  Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.functions.Winnow
  Outputs the prediction for the given instance.
classifyInstance(Instance) - Method in class weka.classifiers.lazy.IB1
  Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.meta.AdditiveRegression
  Classify an instance.
classifyInstance(Instance) - Method in class weka.classifiers.meta.RegressionByDiscretization
  Returns a predicted class for the test instance.
classifyInstance(Instance) - Method in class weka.classifiers.rules.NNge
  Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.rules.OneR
  Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.rules.part.ClassifierDecList
  Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.rules.PART
  Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.rules.part.MakeDecList
  Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.rules.Prism
  Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.rules.Ridor
  Classify the test instance with the rule learner
classifyInstance(Instance) - Method in class weka.classifiers.rules.ZeroR
  Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.Id3
  Classifies a given test instance using the decision tree.
classifyInstance(Instance) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
  Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.j48.ClassifierTree
  Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.J48
  Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.LMT
  Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.m5.M5Base
  Calculates a prediction for an instance using a set of rules or an M5 model tree
classifyInstance(Instance) - Method in class weka.classifiers.trees.m5.PreConstructedLinearModel
  Predicts the class of the supplied instance using the linear model.
classifyInstance(Instance) - Method in class weka.classifiers.trees.m5.Rule
  Calculates a prediction for an instance using this rule or M5 model tree
classifyInstance(Instance) - Method in class weka.classifiers.trees.m5.RuleNode
  Classify an instance using this node.
classifyInstance(Instance) - Method in class weka.classifiers.trees.NBTree
  Classifies an instance.
classIndex() - Method in class weka.core.Instance
  Returns the class attribute's index.
classIndex() - Method in class weka.core.Instances
  Returns the class attribute's index.
classIndexTipText() - Method in class weka.associations.Tertius
  Returns the tip text for this property.
classIndexTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified
  Returns the tip text for this property
classIsMissing() - Method in class weka.core.Instance
  Tests if an instance's class is missing.
className(int) - Method in class weka.classifiers.evaluation.ConfusionMatrix
  Gets the name of one of the classes.
classNameTipText() - Method in class weka.filters.unsupervised.attribute.NumericTransform
  Returns the tip text for this property
ClassOrder - Class in weka.filters.supervised.attribute
  A filter that sorts the order of classes so that the class values are no longer of in the order of that in the header file after filtered.
ClassOrder() - Constructor for class weka.filters.supervised.attribute.ClassOrder
classOrderTipText() - Method in class weka.filters.supervised.attribute.ClassOrder
  Returns the tip text for this property
ClassPanel - Class in weka.gui.visualize
  This panel displays coloured labels for nominal attributes and a spectrum for numeric attributes.
ClassPanel() - Constructor for class weka.gui.visualize.ClassPanel
classProb(int, Instance, int) - Method in class weka.classifiers.trees.j48.BinC45Split
  Gets class probability for instance.
classProb(int, Instance, int) - Method in class weka.classifiers.trees.j48.C45Split
  Gets class probability for instance.
classProb(int, Instance, int) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
  Gets class probability for instance.
classProb(int, Instance, int) - Method in class weka.classifiers.trees.j48.NBTreeNoSplit
  Return the probability for a class value
classProb(int, Instance, int) - Method in class weka.classifiers.trees.j48.NBTreeSplit
  Return the probability for a class value
classProbLaplace(int, Instance, int) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
  Gets class probability for instance.
classValue() - Method in class weka.core.Instance
  Returns an instance's class value in internal format.
ClassValuePicker - Class in weka.gui.beans
ClassValuePicker() - Constructor for class weka.gui.beans.ClassValuePicker
ClassValuePickerBeanInfo - Class in weka.gui.beans
  BeanInfo class for the class value picker bean
ClassValuePickerBeanInfo() - Constructor for class weka.gui.beans.ClassValuePickerBeanInfo
ClassValuePickerCustomizer - Class in weka.gui.beans
ClassValuePickerCustomizer() - Constructor for class weka.gui.beans.ClassValuePickerCustomizer
clean() - Method in class weka.classifiers.functions.supportVector.CachedKernel
  Frees the cache used by the kernel.
clean() - Method in class weka.classifiers.functions.supportVector.Kernel
  Frees the memory used by the kernel.
cleanup(Instances) - Method in class weka.classifiers.rules.part.ClassifierDecList
  Cleanup in order to save memory.
cleanUp() - Method in class weka.classifiers.rules.RuleStats
  Frees up memory after classifier has been built.
cleanup() - Method in class weka.classifiers.trees.j48.BinC45ModelSelection
  Sets reference to training data to null.
cleanup() - Method in class weka.classifiers.trees.j48.C45ModelSelection
  Sets reference to training data to null.
cleanup(Instances) - Method in class weka.classifiers.trees.j48.ClassifierTree
  Cleanup in order to save memory.
cleanup() - Method in class weka.classifiers.trees.j48.NBTreeModelSelection
  Sets reference to training data to null.
cleanup() - Method in class weka.classifiers.trees.lmt.LMTNode
  Cleanup in order to save memory.
cleanup() - Method in class weka.classifiers.trees.lmt.LogisticBase
  Cleanup in order to save memory.
cleanup() - Method in class weka.classifiers.trees.lmt.ResidualModelSelection
  Method not in use
clear() - Method in class weka.associations.tertius.SimpleLinkedList
clear() - Method in class weka.classifiers.lazy.kstar.KStarCache.CacheTable
  Clears this hashtable so that it contains no keys.
clear() - Method in class weka.classifiers.xml.XMLClassifier
  generates internally a new XML document and clears also the IgnoreList and the mappings for the Read/Write-Methods
clear() - Method in class weka.core.ProtectedProperties
  Overrides a method to prevent the properties from being modified.
clear() - Method in class weka.core.xml.MethodHandler
  removes all mappings
clear() - Method in class weka.core.xml.XMLBasicSerialization
  generates internally a new XML document and clears also the IgnoreList and the mappings for the Read/Write-Methods
clear() - Method in class weka.core.xml.XMLDocument
  sets up an empty DOM document, with the current DOCTYPE and root node
clear() - Method in class weka.core.xml.XMLSerialization
  generates internally a new XML document and clears also the IgnoreList and the mappings for the Read/Write-Methods
clear() - Method in class weka.core.xml.XMLSerializationMethodHandler
  removes all current methods and adds the methods according to the
clear() - Method in class weka.experiment.xml.XMLExperiment
  generates internally a new XML document and clears also the IgnoreList and the mappings for the Read/Write-Methods
clear() - Method in class weka.gui.beans.xml.XMLBeans
  generates internally a new XML document and clears also the IgnoreList and the mappings for the Read/Write-Methods
clearLayout() - Method in class weka.gui.beans.KnowledgeFlowApp
clearRect(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
  Draw a filled rectangle with the background color.
clearResults() - Method in class weka.gui.ResultHistoryPanel
  Removes all of the result buffers from the history.
clearSearch() - Method in class weka.gui.arffviewer.ArffPanel
  clears the search, i.e.
clearSearch() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  clears the search, i.e.
clearUndo() - Method in interface weka.core.Undoable
  removes the undo history
clearUndo() - Method in class weka.gui.arffviewer.ArffPanel
  removes the undo history
clearUndo() - Method in class weka.gui.arffviewer.ArffTableModel
  removes the undo history
clearUndo() - Method in class weka.gui.arffviewer.ArffTableSorter
  removes the undo history
clip(Shape) - Method in class weka.gui.visualize.PostscriptGraphics
clipRect(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
  Not implemented
clone() - Method in class weka.associations.tertius.LiteralSet
  Returns a shallow copy of this set.
clone() - Method in class weka.associations.tertius.Rule
  Returns a shallow copy of this rule.
clone() - Method in class weka.classifiers.evaluation.ConfusionMatrix
  Creates and returns a clone of this object.
clone() - Method in class weka.classifiers.functions.pace.DiscreteFunction
  Clones the discrete function
clone() - Method in class weka.classifiers.functions.pace.DoubleVector
  Clones the DoubleVector object.
clone() - Method in class weka.classifiers.functions.pace.IntVector
  Clones the IntVector object.
clone() - Method in class weka.classifiers.functions.pace.Matrix
  Clone the Matrix object.
clone() - Method in class weka.classifiers.functions.pace.PaceMatrix
  Clone the PaceMatrix object.
clone() - Method in interface weka.classifiers.IterativeClassifier
  Performs a deep copy of the classifier, and a reference copy of the training instances (or a deep copy if required).
clone() - Method in class weka.classifiers.trees.ADTree
  Creates a clone that is identical to the current tree, but is independent.
clone() - Method in class weka.classifiers.trees.adtree.PredictionNode
  Clones this node.
clone() - Method in class weka.classifiers.trees.adtree.Splitter
  Clones this node.
clone() - Method in class weka.classifiers.trees.adtree.TwoWayNominalSplit
  Clones this node.
clone() - Method in class weka.classifiers.trees.adtree.TwoWayNumericSplit
  Clones this node.
clone() - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
  Allows to clone a model (shallow copy).
clone() - Method in class weka.classifiers.trees.j48.Distribution
  Clones distribution (Deep copy of distribution).
clone() - Method in class weka.core.Matrix
  Deprecated. Creates and returns a clone of this object.
clone() - Method in class weka.core.matrix.Matrix
  Clone the Matrix object.
close() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  closes the window, i.e., if the parent is not null and implements the WindowListener interface it calls the windowClosing method
closeAllFiles() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  closes all open files
closeFile() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  closes the current tab
closeFile(boolean) - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  closes the current tab
Clusterer - Class in weka.clusterers
  Abstract clusterer.
Clusterer() - Constructor for class weka.clusterers.Clusterer
Clusterer - Class in weka.gui.beans
  Bean that wraps around weka.clusterers
Clusterer() - Constructor for class weka.gui.beans.Clusterer
  Creates a new `Clusterer` instance.
ClustererBeanInfo - Class in weka.gui.beans
  BeanInfo class for the Clusterer wrapper bean
ClustererBeanInfo() - Constructor for class weka.gui.beans.ClustererBeanInfo
ClustererCustomizer - Class in weka.gui.beans
  GUI customizer for the Clusterer wrapper bean
ClustererCustomizer() - Constructor for class weka.gui.beans.ClustererCustomizer
ClustererPanel - Class in weka.gui.explorer
  This panel allows the user to select and configure a clusterer, and evaluate the clusterer using a number of testing modes (test on the training data, train/test on a percentage split, test on a separate split).
ClustererPanel() - Constructor for class weka.gui.explorer.ClustererPanel
  Creates the clusterer panel
ClustererPerformanceEvaluator - Class in weka.gui.beans
  A bean that evaluates the performance of batch trained clusterers
ClustererPerformanceEvaluator() - Constructor for class weka.gui.beans.ClustererPerformanceEvaluator
ClustererPerformanceEvaluatorBeanInfo - Class in weka.gui.beans
  Bean info class for the clusterer performance evaluator
ClustererPerformanceEvaluatorBeanInfo() - Constructor for class weka.gui.beans.ClustererPerformanceEvaluatorBeanInfo
clustererTipText() - Method in class weka.filters.unsupervised.attribute.AddCluster
  Returns the tip text for this property
clustererTipText() - Method in class weka.filters.unsupervised.attribute.ClusterMembership
  Returns a description of this option suitable for display as a tip text in the gui.
ClusterEvaluation - Class in weka.clusterers
  Class for evaluating clustering models.
ClusterEvaluation() - Constructor for class weka.clusterers.ClusterEvaluation
  Constructor.
ClusterGenerator - Class in weka.datagenerators
  Abstract class for cluster data generators.
ClusterGenerator() - Constructor for class weka.datagenerators.ClusterGenerator
clusteringSeedTipText() - Method in class weka.classifiers.functions.RBFNetwork
  Returns the tip text for this property
clusterInstance(Instance) - Method in class weka.clusterers.Clusterer
  Classifies a given instance.
clusterInstance(Instance) - Method in class weka.clusterers.Cobweb
  Classifies a given instance.
clusterInstance(Instance) - Method in class weka.clusterers.FarthestFirst
  Classifies a given instance.
clusterInstance(Instance) - Method in class weka.clusterers.SimpleKMeans
  Classifies a given instance.
ClusterMembership - Class in weka.filters.unsupervised.attribute
  A filter that uses a clusterer to obtain cluster membership values for each input instance and outputs them as new instances.
ClusterMembership() - Constructor for class weka.filters.unsupervised.attribute.ClusterMembership
clusterPriors() - Method in class weka.clusterers.DensityBasedClusterer
  Returns the prior probability of each cluster.
clusterPriors() - Method in class weka.clusterers.EM
  Returns the cluster priors.
clusterPriors() - Method in class weka.clusterers.MakeDensityBasedClusterer
  Returns the cluster priors.
clusterResultsToString() - Method in class weka.clusterers.ClusterEvaluation
  return the results of clustering.
Cobweb - Class in weka.clusterers
  Class implementing the Cobweb and Classit clustering algorithms.
Cobweb() - Constructor for class weka.clusterers.Cobweb
cochransCriterion(double[][]) - Static method in class weka.core.ContingencyTables
  Tests if Cochran's criterion is fullfilled for the given contingency table.
codingCost() - Method in class weka.classifiers.trees.j48.C45Split
  Returns coding cost for split (used in rule learner).
codingCost() - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
  Returns coding costs of model.
coefficients() - Method in class weka.classifiers.functions.LinearRegression
  Returns the coefficients for this linear model.
coefficients() - Method in class weka.classifiers.functions.PaceRegression
  Returns the coefficients for this linear model.
coefficients() - Method in class weka.classifiers.trees.m5.PreConstructedLinearModel
  Return the array of coefficients
collapse() - Method in class weka.classifiers.trees.j48.C45PruneableClassifierTree
  Collapses a tree to a node if training error doesn't increase.
Colors - Class in weka.gui.treevisualizer
  This class maintains a list that contains all the colornames from the dotty standard and what color (in RGB) they represent
Colors() - Constructor for class weka.gui.treevisualizer.Colors
columnResponseExplanation(PaceMatrix, IntVector, int, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Returns the squared ks-th response value if the j-th column becomes the ks-th after orthogonal transformation.
combinations(int, int) - Static method in class weka.classifiers.functions.LeastMedSq
  Produces the combination nCr
combinedDL(double, double) - Method in class weka.classifiers.rules.RuleStats
  Compute the combined DL of the ruleset in this class, i.e.
compactify() - Method in class weka.core.Instances
  Compactifies the set of instances.
compare(Object, Object) - Method in class weka.core.InstanceComparator
  compares the two instances, returns -1 if o1 is smaller than o2, 0 if equal and +1 if greater.
compare(Object, Object) - Method in class weka.core.RTSI.StringCompare
  Compares its two arguments for order.
compare(int, int) - Method in class weka.gui.TableSorter
compareOptions(String[], String[]) - Static method in class weka.core.CheckOptionHandler
  Compares the two given sets of options.
compareRowsByColumn(int, int, int) - Method in class weka.gui.TableSorter
compareTo(Object) - Method in class weka.associations.RuleItem
  compares two RuleItems and allows an ordering concerning expected predictive accuracy and time of generation Note: this class has a natural ordering that is inconsistent with equals
compareTo(Object) - Method in class weka.core.Version
  checks the version of this class against the given version-string
comparisonString(int, Instances) - Method in class weka.classifiers.trees.adtree.Splitter
  Gets the string describing the comparision the split depends on for a particular branch.
comparisonString(int, Instances) - Method in class weka.classifiers.trees.adtree.TwoWayNominalSplit
  Gets the string describing the comparision the split depends on for a particular branch.
comparisonString(int, Instances) - Method in class weka.classifiers.trees.adtree.TwoWayNumericSplit
  Gets the string describing the comparision the split depends on for a particular branch.
ComplementNaiveBayes - Class in weka.classifiers.bayes
  Class for building and using a Complement class Naive Bayes classifier.
ComplementNaiveBayes() - Constructor for class weka.classifiers.bayes.ComplementNaiveBayes
complexityParameterTipText() - Method in class weka.attributeSelection.SVMAttributeEval
  Returns a tip text for this property suitable for display in the GUI
ComponentHelper - Class in weka.gui
  A helper class for some common tasks with Dialogs, Icons, etc.
ComponentHelper() - Constructor for class weka.gui.ComponentHelper
Compute - Interface in weka.experiment
  Interface to something that can accept remote connections and execute a task.
cond() - Method in class weka.core.matrix.Matrix
  Matrix condition (2 norm)
cond() - Method in class weka.core.matrix.SingularValueDecomposition
  Two norm condition number
ConditionalEstimator - Interface in weka.estimators
  Interface for conditional probability estimators.
confidenceFactorTipText() - Method in class weka.classifiers.rules.PART
  Returns the tip text for this property
confidenceFactorTipText() - Method in class weka.classifiers.trees.J48
  Returns the tip text for this property
confidenceForRule(AprioriItemSet, AprioriItemSet) - Static method in class weka.associations.AprioriItemSet
  Outputs the confidence for a rule.
confirmationComparator - Static variable in class weka.associations.tertius.Rule
  Comparator used to compare two rules according to their confirmation value.
confirmationThenObservedComparator - Static variable in class weka.associations.tertius.Rule
  Comparator used to compare two rules according to their confirmation and then their observed number of counter-instances.
confirmationThresholdTipText() - Method in class weka.associations.Tertius
  Returns the tip text for this property.
confirmationValuesTipText() - Method in class weka.associations.Tertius
  Returns the tip text for this property.
ConfusionMatrix - Class in weka.classifiers.evaluation
  Cells of this matrix correspond to counts of the number (or weight) of predictions for each actual value / predicted value combination.
confusionMatrix() - Method in class weka.classifiers.Evaluation
  Returns a copy of the confusion matrix.
ConfusionMatrix(String[]) - Constructor for class weka.classifiers.evaluation.ConfusionMatrix
  Creates the confusion matrix with the given class names.
ConjunctiveRule - Class in weka.classifiers.rules
  This class implements a single conjunctive rule learner that can predict for numeric and nominal class labels.
ConjunctiveRule() - Constructor for class weka.classifiers.rules.ConjunctiveRule
connect(NeuralConnection, NeuralConnection) - Static method in class weka.classifiers.functions.neural.NeuralConnection
  Connects two units together.
CONNECTED - Static variable in class weka.classifiers.functions.neural.NeuralConnection
  This flag is set once the unit has a connection.
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.AbstractDataSink
  Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.AbstractDataSink
  Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(String) - Method in class weka.gui.beans.AbstractEvaluator
  Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.AbstractEvaluator
  Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.AbstractTestSetProducer
  Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.AbstractTestSetProducer
  Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer
  Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer
  Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.AbstractTrainingSetProducer
  Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.AbstractTrainingSetProducer
  Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in interface weka.gui.beans.BeanCommon
  Returns true if, at this time, the object will accept a connection via the supplied EventSetDescriptor
connectionAllowed(String) - Method in interface weka.gui.beans.BeanCommon
  Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in class weka.gui.beans.ClassAssigner
  Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.ClassAssigner
  Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.Classifier
  Returns true if, at this time, the object will accept a connection with respect to the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Classifier
  Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.ClassValuePicker
  Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.ClassValuePicker
  Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.Clusterer
  Returns true if, at this time, the object will accept a connection with respect to the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Clusterer
  Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.Filter
  Returns true if, at this time, the object will accept a connection with respect to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Filter
  Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.MetaBean
  Returns true if, at this time, the object will accept a connection with respect to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.MetaBean
connectionAllowed(String) - Method in class weka.gui.beans.PredictionAppender
  Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.PredictionAppender
  Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.StripChart
  Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.StripChart
  Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionNotification(String, Object) - Method in class weka.gui.beans.AbstractDataSink
  Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.AbstractEvaluator
  Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.AbstractTestSetProducer
  Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer
  Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.AbstractTrainingSetProducer
  Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in interface weka.gui.beans.BeanCommon
  Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.ClassAssigner
  Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.Classifier
  Notify this object that it has been registered as a listener with a source with respect to the named event
connectionNotification(String, Object) - Method in class weka.gui.beans.ClassValuePicker
  Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.Clusterer
  Notify this object that it has been registered as a listener with a source with respect to the named event
connectionNotification(String, Object) - Method in class weka.gui.beans.Filter
  Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.MetaBean
  Notify this object that it has been registered as a listener with a source with respect to the named event.
connectionNotification(String, Object) - Method in class weka.gui.beans.PredictionAppender
  Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.StripChart
  Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
CONNECTIONS - Static variable in class weka.gui.beans.BeanConnection
  The list of connections
connectToDatabase() - Method in class weka.core.converters.DatabaseLoader
  Opens a connection to the database
connectToDatabase() - Method in class weka.core.converters.DatabaseSaver
  Opens a connection to the database
connectToDatabase() - Method in class weka.experiment.DatabaseUtils
  Opens a connection to the database
consequence() - Method in class weka.associations.RuleItem
  Gets the consequence of a rule
ConsistencySubsetEval - Class in weka.attributeSelection
  Consistency attribute subset evaluator.
ConsistencySubsetEval() - Constructor for class weka.attributeSelection.ConsistencySubsetEval
  Constructor.
ConsistencySubsetEval.hashKey - Class in weka.attributeSelection
  Class providing keys to the hash table.
ConsistencySubsetEval.hashKey(Instance, int) - Constructor for class weka.attributeSelection.ConsistencySubsetEval.hashKey
  Constructor for a hashKey
ConsistencySubsetEval.hashKey(double[]) - Constructor for class weka.attributeSelection.ConsistencySubsetEval.hashKey
  Constructor for a hashKey
CONST_AUTOMATIC_SHAPE - Static variable in class weka.gui.visualize.Plot2D
constructWithCopy(double[][]) - Static method in class weka.classifiers.functions.pace.Matrix
  Construct a matrix from a copy of a 2-D array.
constructWithCopy(double[][]) - Static method in class weka.core.matrix.Matrix
  Construct a matrix from a copy of a 2-D array.
containedBy(Instance) - Method in class weka.associations.ItemSet
  Checks if an instance contains an item set.
contains(Literal) - Method in class weka.associations.tertius.LiteralSet
  Test if this LiteralSet contains a given Literal.
contains(int) - Method in class weka.classifiers.bayes.net.ParentSet
  test if node is contained in parent set
contains(int) - Method in class weka.classifiers.functions.supportVector.SMOset
  Checks whether an element is in the set.
contains(Object) - Method in class weka.core.FastVector
  added by akibriya
contains(String) - Method in class weka.core.xml.MethodHandler
  checks whether a method is stored for the given property
contains(Class) - Method in class weka.core.xml.MethodHandler
  checks whether a method is stored for the given class
contains(String) - Method in class weka.gui.HierarchyPropertyParser
  Whether the HierarchyPropertyParser contains the given string
containsKey(double) - Method in class weka.classifiers.lazy.kstar.KStarCache.CacheTable
  Tests if the specified double is a key in this hashtable.
containsKey(double) - Method in class weka.classifiers.lazy.kstar.KStarCache
  Checks if the specified key maps with an entry in the cache table
context() - Method in class weka.gui.HierarchyPropertyParser
  The context of the current node, i.e.
ContingencyTables - Class in weka.core
  Class implementing some statistical routines for contingency tables.
ContingencyTables() - Constructor for class weka.core.ContingencyTables
ConverterUtils - Class in weka.core.converters
  Utility routines for the converter package.
ConverterUtils() - Constructor for class weka.core.converters.ConverterUtils
convertInstance(Instance) - Method in interface weka.attributeSelection.AttributeTransformer
  Transforms an instance in the format of the original data to the transformed space
convertInstance(Instance) - Method in class weka.attributeSelection.PrincipalComponents
  Transform an instance in original (unormalized) format.
convertNewLines(String) - Static method in class weka.core.Utils
  Converts carriage returns and new lines in a string into \r and \n.
convertNominalTipText() - Method in class weka.classifiers.trees.LMT
  Returns the tip text for this property
convertToAttribX(double) - Method in class weka.gui.visualize.Plot2D
  convert a Panel x coordinate to a raw x value.
convertToAttribY(double) - Method in class weka.gui.visualize.Plot2D
  convert a Panel y coordinate to a raw y value.
convertToPanelX(double) - Method in class weka.gui.visualize.Plot2D
  Convert an raw x value to Panel x coordinate.
convertToPanelY(double) - Method in class weka.gui.visualize.Plot2D
  Convert an raw y value to Panel y coordinate.
convictionForRule(AprioriItemSet, AprioriItemSet, int, int) - Method in class weka.associations.AprioriItemSet
  Outputs the conviction for a rule.
copy() - Method in class weka.associations.tertius.IndividualInstance
copy(ParentSet) - Method in class weka.classifiers.bayes.net.ParentSet
  Copy makes current parents set equal to other parent set
copy() - Method in class weka.classifiers.functions.pace.DoubleVector
  Makes a deep copy of the vector
copy() - Method in class weka.classifiers.functions.pace.IntVector
  Makes a deep copy of the vector
copy() - Method in class weka.classifiers.functions.pace.Matrix
  Make a deep copy of a matrix
copy() - Method in class weka.classifiers.rules.Rule
  Get a shallow copy of this rule
copy() - Method in class weka.classifiers.trees.m5.CorrelationSplitInfo
  Makes a copy of this CorrelationSplitInfo object
copy() - Method in interface weka.classifiers.trees.m5.SplitEvaluate
  makes a copy of the SplitEvaluate object
copy() - Method in class weka.classifiers.trees.m5.YongSplitInfo
  Makes a copy of this SplitInfo object
copy() - Method in class weka.core.Attribute
  Produces a shallow copy of this attribute.
copy() - Method in class weka.core.BinarySparseInstance
  Produces a shallow copy of this instance.
copy() - Method in interface weka.core.Copyable
  This method produces a shallow copy of an object.
copy() - Method in class weka.core.FastVector
  Produces a shallow copy of this vector.
copy() - Method in class weka.core.Instance
  Produces a shallow copy of this instance.
copy() - Method in class weka.core.matrix.Matrix
  Make a deep copy of a matrix
copy() - Method in class weka.core.SparseInstance
  Produces a shallow copy of this instance.
Copy - Class in weka.filters.unsupervised.attribute
  An instance filter that copies a range of attributes in the dataset.
Copy() - Constructor for class weka.filters.unsupervised.attribute.Copy
Copyable - Interface in weka.core
  Interface implemented by classes that can produce "shallow" copies of their objects.
copyArea(int, int, int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
  Not implemented
copyContent() - Method in class weka.gui.arffviewer.ArffPanel
  copies the content of the selection to the clipboard
copyContent() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  copies the content of the selection to the clipboard
copyElements() - Method in class weka.core.FastVector
  Clones the vector and shallow copies all its elements.
correct() - Method in class weka.classifiers.evaluation.ConfusionMatrix
  Gets the number of correct classifications (that is, for which a correct prediction was made).
correct() - Method in class weka.classifiers.Evaluation
  Gets the number of instances correctly classified (that is, for which a correct prediction was made).
correlation(double[], double[], int) - Static method in class weka.core.Utils
  Returns the correlation coefficient of two double vectors.
correlation - Variable in class weka.experiment.PairedStats
  The correlation coefficient
correlationCoefficient() - Method in class weka.classifiers.Evaluation
  Returns the correlation coefficient if the class is numeric.
CorrelationSplitInfo - Class in weka.classifiers.trees.m5
  Finds split points using correlation.
CorrelationSplitInfo(int, int, int) - Constructor for class weka.classifiers.trees.m5.CorrelationSplitInfo
  Constructs an object which contains the split information
CostCurve - Class in weka.classifiers.evaluation
  Generates points illustrating probablity cost tradeoffs that can be obtained by varying the threshold value between classes.
CostCurve() - Constructor for class weka.classifiers.evaluation.CostCurve
CostMatrix - Class in weka.classifiers
  Class for storing and manipulating a misclassification cost matrix.
CostMatrix(CostMatrix) - Constructor for class weka.classifiers.CostMatrix
  Creates a cost matrix that is a copy of another.
CostMatrix(int) - Constructor for class weka.classifiers.CostMatrix
  Creates a default cost matrix of a particular size.
CostMatrix(Reader) - Constructor for class weka.classifiers.CostMatrix
  Creates a cost matrix from a reader.
CostMatrixEditor - Class in weka.gui
  Class for editing CostMatrix objects.
CostMatrixEditor() - Constructor for class weka.gui.CostMatrixEditor
  Constructs a new CostMatrixEditor.
costMatrixSourceTipText() - Method in class weka.classifiers.meta.CostSensitiveClassifier
costMatrixSourceTipText() - Method in class weka.classifiers.meta.MetaCost
  Returns the tip text for this property
costMatrixTipText() - Method in class weka.classifiers.meta.CostSensitiveClassifier
costMatrixTipText() - Method in class weka.classifiers.meta.MetaCost
  Returns the tip text for this property
CostSensitiveClassifier - Class in weka.classifiers.meta
  This metaclassifier makes its base classifier cost-sensitive.
CostSensitiveClassifier() - Constructor for class weka.classifiers.meta.CostSensitiveClassifier
  Default constructor.
CostSensitiveClassifierSplitEvaluator - Class in weka.experiment
  A SplitEvaluator that produces results for a classification scheme on a nominal class attribute, including weighted misclassification costs.
CostSensitiveClassifierSplitEvaluator() - Constructor for class weka.experiment.CostSensitiveClassifierSplitEvaluator
count() - Method in class weka.associations.RuleGeneration
  Gets the actual maximum value of the generation time
count - Variable in class weka.experiment.PairedStats
  The number of data points seen
count - Variable in class weka.experiment.Stats
  The number of values seen
countData() - Method in class weka.classifiers.rules.RuleStats
  Filter the data according to the ruleset and compute the basic stats: coverage/uncoverage, true/false positive/negatives of each rule
countData(int, Instances, double[][]) - Method in class weka.classifiers.rules.RuleStats
  Count data from the position index in the ruleset assuming that given data are not covered by the rules in position 0...(index-1), and the statistics of these rules are provided.
  This procedure is typically useful when a temporary object of RuleStats is constructed in order to efficiently calculate the relative DL of rule in position index, thus all other stuff is not needed.
counter() - Method in class weka.associations.ItemSet
  Gets the counter
counterInstance(Instance, Instance) - Method in class weka.associations.tertius.LiteralSet
  Test if an individual instance, given a part instance of this individual, is a counter-instance of this LiteralSet.
counterInstance(Instance) - Method in class weka.associations.tertius.LiteralSet
  Test if an instance is a counter-instance of this LiteralSet.
counterInstance(Instance) - Method in class weka.associations.tertius.Rule
  Test if an instance is a counter-instance of this rule.
countsForInstance(Instance) - Method in class weka.classifiers.bayes.BayesNet
  Calculates the counts for Dirichlet distribution for the class membership probabilities for the given test instance.
covers(Instance) - Method in class weka.classifiers.rules.Rule
  Whether the instance covered by this rule
CramersV(double[][]) - Static method in class weka.core.ContingencyTables
  Computes Cramer's V for a contingency table.
create(Reader) - Method in class weka.gui.treevisualizer.TreeBuild
  This will build A node structure from the dotty format passed.
create() - Method in class weka.gui.visualize.PostscriptGraphics
  Clone a PostscriptGraphics object
createExperimentIndex() - Method in class weka.experiment.DatabaseUtils
  Attempts to create the experiment index table
createExperimentIndexEntry(ResultProducer) - Method in class weka.experiment.DatabaseUtils
  Attempts to insert a results entry for the table into the experiment index.
createResultsTable(ResultProducer, String) - Method in class weka.experiment.DatabaseUtils
  Creates a results table for the supplied result producer.
createSingleton(String[]) - Static method in class weka.gui.beans.KnowledgeFlowApp
  Create the singleton instance of the KnowledgeFlow
crossoverProbTipText() - Method in class weka.attributeSelection.GeneticSearch
  Returns the tip text for this property
crossValidate(NaiveBayesUpdateable, Instances, Random) - Static method in class weka.classifiers.trees.j48.NBTreeNoSplit
  Utility method for fast 5-fold cross validation of a naive bayes model
CrossValidateAttributes() - Method in class weka.attributeSelection.AttributeSelection
  Perform a cross validation for attribute selection.
crossValidateModel(Classifier, Instances, int, Random) - Method in class weka.classifiers.Evaluation
  Performs a (stratified if class is nominal) cross-validation for a classifier on a set of instances.
crossValidateModel(String, Instances, int, String[], Random) - Method in class weka.classifiers.Evaluation
  Performs a (stratified if class is nominal) cross-validation for a classifier on a set of instances.
crossValidateModel(DensityBasedClusterer, Instances, int, Random) - Static method in class weka.clusterers.ClusterEvaluation
  Perform a cross-validation for DensityBasedClusterer on a set of instances.
crossValidateModel(String, Instances, int, String[], Random) - Static method in class weka.clusterers.ClusterEvaluation
  Performs a cross-validation for a DensityBasedClusterer clusterer on a set of instances.
crossValidateTipText() - Method in class weka.classifiers.lazy.IBk
  Returns the tip text for this property
CrossValidationFoldMaker - Class in weka.gui.beans
  Bean for splitting instances into training ant test sets according to a cross validation
CrossValidationFoldMaker() - Constructor for class weka.gui.beans.CrossValidationFoldMaker
CrossValidationFoldMakerBeanInfo - Class in weka.gui.beans
  BeanInfo class for the cross validation fold maker bean
CrossValidationFoldMakerBeanInfo() - Constructor for class weka.gui.beans.CrossValidationFoldMakerBeanInfo
CrossValidationFoldMakerCustomizer - Class in weka.gui.beans
  GUI Customizer for the cross validation fold maker bean
CrossValidationFoldMakerCustomizer() - Constructor for class weka.gui.beans.CrossValidationFoldMakerCustomizer
CrossValidationResultProducer - Class in weka.experiment
  Generates for each run, carries out an n-fold cross-validation, using the set SplitEvaluator to generate some results.
CrossValidationResultProducer() - Constructor for class weka.experiment.CrossValidationResultProducer
crossValTipText() - Method in class weka.classifiers.rules.DecisionTable
  Returns the tip text for this property
CSVLoader - Class in weka.core.converters
  Reads a text file that is comma or tab delimited..
CSVLoader() - Constructor for class weka.core.converters.CSVLoader
CSVResultListener - Class in weka.experiment
  CSVResultListener outputs the received results in csv format to a Writer
CSVResultListener() - Constructor for class weka.experiment.CSVResultListener
  Sets temporary file.
CSVSaver - Class in weka.core.converters
  Writes to a destination in csv format.
CSVSaver() - Constructor for class weka.core.converters.CSVSaver
  Constructor
cTipText() - Method in class weka.classifiers.functions.SMO
  Returns the tip text for this property
cTipText() - Method in class weka.classifiers.functions.SMOreg
  Returns the tip text for this property
cumulate() - Method in class weka.classifiers.functions.pace.DoubleVector
  Returns a vector that stores the cumulated values of the original vector
cumulateInPlace() - Method in class weka.classifiers.functions.pace.DoubleVector
  Cumulates the original vector in place
cumulativeCV(BayesNet) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
  CumulativeCV returns the accuracy calculated using cumulative cross validation.
CustomizerCloseRequester - Interface in weka.gui.beans
  Customizers who want to be able to close the customizer window themselves can implement this window.
customizerClosing() - Method in class weka.gui.beans.ClassAssignerCustomizer
customizerClosing() - Method in class weka.gui.beans.ClassValuePickerCustomizer
customizerClosing() - Method in interface weka.gui.beans.CustomizerClosingListener
  Customizer classes that want to know when they are being disposed of can implement this method.
CustomizerClosingListener - Interface in weka.gui.beans
CustomPanelSupplier - Interface in weka.gui
  An interface for objects that are capable of supplying their own custom GUI components.
cutoffTipText() - Method in class weka.clusterers.Cobweb
  Returns the tip text for this property
CVParameterSelection - Class in weka.classifiers.meta
  Class for performing parameter selection by cross-validation for any classifier.
CVParameterSelection() - Constructor for class weka.classifiers.meta.CVParameterSelection
CVParametersTipText() - Method in class weka.classifiers.meta.CVParameterSelection
  Returns the tip text for this property
CVResultsString() - Method in class weka.attributeSelection.AttributeSelection
  returns a string summarizing the results of repeated attribute selection runs on splits of a dataset.
CVTypeTipText() - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm

## D

DatabaseConnection - Class in weka.core.converters
  Connects to a database.
DatabaseConnection() - Constructor for class weka.core.converters.DatabaseConnection
  Sets up the database drivers
DatabaseConnectionDialog - Class in weka.gui
  A dialog to enter URL, username and password for a database connection.
DatabaseConnectionDialog(Frame) - Constructor for class weka.gui.DatabaseConnectionDialog
  Create database connection dialog.
DatabaseConnectionDialog(Frame, String, String) - Constructor for class weka.gui.DatabaseConnectionDialog
  Create database connection dialog.
DatabaseConverter - Interface in weka.core.converters
  Marker interface for a loader/saver that uses a database
DatabaseLoader - Class in weka.core.converters
  Reads from a database.
DatabaseLoader() - Constructor for class weka.core.converters.DatabaseLoader
  Constructor
DatabaseResultListener - Class in weka.experiment
  DatabaseResultListener takes the results from a ResultProducer and submits them to a central database.
DatabaseResultListener() - Constructor for class weka.experiment.DatabaseResultListener
  Sets up the database drivers
DatabaseResultProducer - Class in weka.experiment
  DatabaseResultProducer examines a database and extracts out the results produced by the specified ResultProducer and submits them to the specified ResultListener.
DatabaseResultProducer() - Constructor for class weka.experiment.DatabaseResultProducer
  Creates the DatabaseResultProducer, letting the parent constructor do it's thing.
DatabaseSaver - Class in weka.core.converters
  Writes to a database (tested with MySQL, InstantDB, HSQLDB).
DatabaseSaver() - Constructor for class weka.core.converters.DatabaseSaver
  Constructor
databaseURLTipText() - Method in class weka.experiment.DatabaseUtils
  Returns the tip text for this property
DatabaseUtils - Class in weka.experiment
  DatabaseUtils provides utility functions for accessing the experiment database.
DatabaseUtils() - Constructor for class weka.experiment.DatabaseUtils
  Reads properties and sets up the database drivers
dataDL(double, double, double, double, double) - Static method in class weka.classifiers.rules.RuleStats
  The description length of data given the parameters of the data based on the ruleset.
DataFormatListener - Interface in weka.gui.beans
  Listener interface that customizer classes that are interested in data format changes can implement.
DataGenerator - Interface in weka.gui.boundaryvisualizer
  Interface to something that can generate new instances based on a set of input instances
dataset() - Method in class weka.core.Instance
  Returns the dataset this instance has access to.
DATASET_FIELD_NAME - Static variable in class weka.experiment.CrossValidationResultProducer
DATASET_FIELD_NAME - Static variable in class weka.experiment.RandomSplitResultProducer
DataSetEvent - Class in weka.gui.beans
  Event encapsulating a data set
DataSetEvent(Object, Instances) - Constructor for class weka.gui.beans.DataSetEvent
DatasetListPanel - Class in weka.gui.experiment
  This panel controls setting a list of datasets for an experiment to iterate over.
DatasetListPanel(Experiment) - Constructor for class weka.gui.experiment.DatasetListPanel
  Creates the dataset list panel with the given experiment.
DatasetListPanel() - Constructor for class weka.gui.experiment.DatasetListPanel
  Create the dataset list panel initially disabled.
DataSink - Interface in weka.gui.beans
  Indicator interface to something that can store instances to some destination
DataSource - Interface in weka.gui.beans
  Interface to something that is capable of being a source for data - either batch or incremental data
DataSourceListener - Interface in weka.gui.beans
  Interface to something that can accept DataSetEvents
DATATYPE_LAYOUT - Static variable in class weka.gui.beans.xml.XMLBeans
  the data that is about to be read/written contains a complete layout
DATATYPE_USERCOMPONENTS - Static variable in class weka.gui.beans.xml.XMLBeans
  the data that is about to be read/written contains user-components, i.e., Metabeans
DataVisualizer - Class in weka.gui.beans
  Bean that encapsulates weka.gui.visualize.VisualizePanel
DataVisualizer() - Constructor for class weka.gui.beans.DataVisualizer
DataVisualizerBeanInfo - Class in weka.gui.beans
  Bean info class for the data visualizer
DataVisualizerBeanInfo() - Constructor for class weka.gui.beans.DataVisualizerBeanInfo
DATE - Static variable in class weka.core.Attribute
  Constant set for attributes with date values.
DATE - Static variable in class weka.core.converters.DatabaseLoader
DATE - Static variable in class weka.experiment.DatabaseUtils
  Type mapping for DATE used for reading experiment results
dateFormatTipText() - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat
DbConnectionDialog(String, String) - Method in class weka.gui.DatabaseConnectionDialog
  Display the database connection dialog
dchisq(double) - Static method in class weka.classifiers.functions.pace.Maths
  Returns the density of the Chi-squared distribution.
dchisq(double, double) - Static method in class weka.classifiers.functions.pace.Maths
  Returns the density of the noncentral Chi-squared distribution.
dchisq(double, DoubleVector) - Static method in class weka.classifiers.functions.pace.Maths
  Returns the density of the noncentral Chi-squared distribution.
dchisqLog(double) - Static method in class weka.classifiers.functions.pace.Maths
  Returns the log-density of the noncentral Chi-square distribution.
dchisqLog(double, double) - Static method in class weka.classifiers.functions.pace.Maths
  Returns the log-density value of a noncentral Chi-square distribution.
dchisqLog(double, DoubleVector) - Static method in class weka.classifiers.functions.pace.Maths
  Returns the log-density of a set of noncentral Chi-squared distributions.
DDConditionalEstimator - Class in weka.estimators
  Conditional probability estimator for a discrete domain conditional upon a discrete domain.
DDConditionalEstimator(int, int, boolean) - Constructor for class weka.estimators.DDConditionalEstimator
  Constructor
debugTipText() - Method in class weka.attributeSelection.RaceSearch
  Returns the tip text for this property
debugTipText() - Method in class weka.classifiers.Classifier
  Returns the tip text for this property
debugTipText() - Method in class weka.classifiers.functions.LinearRegression
  Returns the tip text for this property
debugTipText() - Method in class weka.classifiers.functions.Logistic
  Returns the tip text for this property
debugTipText() - Method in class weka.classifiers.functions.PaceRegression
  Returns the tip text for this property
debugTipText() - Method in class weka.classifiers.meta.MultiScheme
  Returns the tip text for this property
debugTipText() - Method in class weka.classifiers.rules.JRip
  Returns the tip text for this property
debugTipText() - Method in class weka.classifiers.trees.RandomTree
  Returns the tip text for this property
debugTipText() - Method in class weka.experiment.DatabaseUtils
  Returns the tip text for this property
debugTipText() - Method in class weka.filters.unsupervised.attribute.AddExpression
  Returns the tip text for this property
decayTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
DecisionStump - Class in weka.classifiers.trees
  Class for building and using a decision stump.
DecisionStump() - Constructor for class weka.classifiers.trees.DecisionStump
DecisionTable - Class in weka.classifiers.rules
  Class for building and using a simple decision table majority classifier.
DecisionTable() - Constructor for class weka.classifiers.rules.DecisionTable
  Constructor for a DecisionTable
DecisionTable.hashKey - Class in weka.classifiers.rules
  Class providing keys to the hash table
DecisionTable.hashKey(Instance, int, boolean) - Constructor for class weka.classifiers.rules.DecisionTable.hashKey
  Constructor for a hashKey
DecisionTable.hashKey(double[]) - Constructor for class weka.classifiers.rules.DecisionTable.hashKey
  Constructor for a hashKey
DecisionTable.Link - Class in weka.classifiers.rules
  Class for a node in a linked list.
DecisionTable.Link(BitSet, double) - Constructor for class weka.classifiers.rules.DecisionTable.Link
  The constructor.
DecisionTable.LinkedList - Class in weka.classifiers.rules
  Class for handling a linked list.
DecisionTable.LinkedList() - Constructor for class weka.classifiers.rules.DecisionTable.LinkedList
decompose() - Method in class weka.classifiers.BVDecompose
  Carry out the bias-variance decomposition
decompose() - Method in class weka.classifiers.BVDecomposeSegCVSub
  Carry out the bias-variance decomposition using the sub-sampled cross-validation method.
Decorate - Class in weka.classifiers.meta
  DECORATE is a meta-learner for building diverse ensembles of classifiers by using specially constructed artificial training examples.
Decorate() - Constructor for class weka.classifiers.meta.Decorate
  Constructor.
DEFAULT_COLORS - Static variable in class weka.gui.boundaryvisualizer.BoundaryPanel
DEFAULT_FORMAT - Static variable in class weka.gui.SimpleDateFormatEditor
  the default format
DEFAULT_HEIGHT - Static variable in class weka.gui.arffviewer.ArffViewerMainPanel
  the default for height
DEFAULT_LEFT - Static variable in class weka.gui.arffviewer.ArffViewerMainPanel
  the default for left
DEFAULT_SHAPE_SIZE - Static variable in class weka.gui.visualize.Plot2D
DEFAULT_TOP - Static variable in class weka.gui.arffviewer.ArffViewerMainPanel
  the default for top
DEFAULT_WIDTH - Static variable in class weka.gui.arffviewer.ArffViewerMainPanel
  the default for width
defaultWeightTipText() - Method in class weka.classifiers.functions.Winnow
  Returns the tip text for this property
defineDataFormat() - Method in class weka.datagenerators.BIRCHCluster
  Initializes the format for the dataset produced.
defineDataFormat() - Method in class weka.datagenerators.RDG1
  Initializes the format for the dataset produced.
del(int, Instance) - Method in class weka.classifiers.trees.j48.Distribution
  Deletes given instance from given bag.
delete(int) - Method in class weka.classifiers.functions.supportVector.SMOset
  Deletes an element from the set.
delete() - Method in class weka.core.Instances
  Removes all instances from the set.
delete(int) - Method in class weka.core.Instances
  Removes an instance at the given position from the set.
deleteAttribute() - Method in class weka.gui.arffviewer.ArffPanel
  deletes the currently selected attribute
deleteAttribute(boolean) - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  deletes the current selected Attribute or several chosen ones
deleteAttributeAt(int) - Method in class weka.core.Instance
  Deletes an attribute at the given position (0 to numAttributes() - 1).
deleteAttributeAt(int) - Method in class weka.core.Instances
  Deletes an attribute at the given position (0 to numAttributes() - 1).
deleteAttributeAt(int) - Method in class weka.gui.arffviewer.ArffTableModel
  deletes the attribute at the given col index.
deleteAttributeAt(int, boolean) - Method in class weka.gui.arffviewer.ArffTableModel
  deletes the attribute at the given col index
deleteAttributeAt(int) - Method in class weka.gui.arffviewer.ArffTableSorter
  deletes the attribute at the given col index
deleteAttributes() - Method in class weka.gui.arffviewer.ArffPanel
  deletes the chosen attributes
deleteAttributes(int[]) - Method in class weka.gui.arffviewer.ArffTableModel
  deletes the attributes at the given indices
deleteAttributes(int[]) - Method in class weka.gui.arffviewer.ArffTableSorter
  deletes the attributes at the given indices
deleteInstance() - Method in class weka.gui.arffviewer.ArffPanel
  deletes the currently selected instance
deleteInstance(boolean) - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  deletes the current selected Instance or several chosen ones
deleteInstanceAt(int) - Method in class weka.gui.arffviewer.ArffTableModel
  deletes the instance at the given index
deleteInstanceAt(int, boolean) - Method in class weka.gui.arffviewer.ArffTableModel
  deletes the instance at the given index
deleteInstanceAt(int) - Method in class weka.gui.arffviewer.ArffTableSorter
  deletes the instance at the given index
deleteInstances() - Method in class weka.gui.arffviewer.ArffPanel
  deletes all the currently selected instances
deleteInstances(int[]) - Method in class weka.gui.arffviewer.ArffTableModel
  deletes the instances at the given positions
deleteInstances(int[]) - Method in class weka.gui.arffviewer.ArffTableSorter
  deletes the instances at the given positions
deleteItemSets(FastVector, int, int) - Static method in class weka.associations.ItemSet
  Deletes all item sets that don't have minimum support.
deleteItemSets(FastVector, int, int) - Static method in class weka.associations.LabeledItemSet
  Deletes all item sets that don't have minimum support and have more than maximum support
deleteLastParent(Instances) - Method in class weka.classifiers.bayes.net.ParentSet
  Delete last added parent from parent set and update internals (specifically the cardinality of the parent set)
deleteParent(int, Instances) - Method in class weka.classifiers.bayes.net.ParentSet
  delete node from parent set
deleteStringAttributes() - Method in class weka.core.Instances
  Deletes all string attributes in the dataset.
deleteWithMissing(int) - Method in class weka.core.Instances
  Removes all instances with missing values for a particular attribute from the dataset.
deleteWithMissing(Attribute) - Method in class weka.core.Instances
  Removes all instances with missing values for a particular attribute from the dataset.
deleteWithMissingClass() - Method in class weka.core.Instances
  Removes all instances with a missing class value from the dataset.
delimitersTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Returns the tip text for this property
delRange(int, Instances, int, int) - Method in class weka.classifiers.trees.j48.Distribution
  Deletes all instances in given range from given bag.
deltaTipText() - Method in class weka.associations.Apriori
  Returns the tip text for this property
deltaTipText() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
deltaTipText() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
DensityBasedClusterer - Class in weka.clusterers
  Abstract clustering model that produces (for each test instance) an estimate of the membership in each cluster (ie.
DensityBasedClusterer() - Constructor for class weka.clusterers.DensityBasedClusterer
depth() - Method in class weka.gui.HierarchyPropertyParser
  Get the depth of the tree, i.e.
descendantPopulationSizeTipText() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
descendantPopulationSizeTipText() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
description() - Method in class weka.associations.tertius.Predicate
description() - Method in class weka.core.Option
  Returns the option's description.
designatedClassTipText() - Method in class weka.classifiers.meta.ThresholdSelector
desiredSizeTipText() - Method in class weka.classifiers.meta.Decorate
  Returns the tip text for this property
desiredWeightOfInstancesPerIntervalTipText() - Method in class weka.filters.unsupervised.attribute.Discretize
  Returns the tip text for this property
det() - Method in class weka.core.matrix.LUDecomposition
  Determinant
det() - Method in class weka.core.matrix.Matrix
  Matrix determinant
determineBounds() - Method in class weka.gui.visualize.Plot2D
  Determine the min and max values for axis and colouring attributes
determineColumnConstraints(ResultProducer) - Method in class weka.experiment.AveragingResultProducer
  Determines if there are any constraints (imposed by the destination) on the result columns to be produced by resultProducers.
determineColumnConstraints(ResultProducer) - Method in class weka.experiment.CSVResultListener
  Determines if there are any constraints (imposed by the destination) on the result columns to be produced by resultProducers.
determineColumnConstraints(ResultProducer) - Method in class weka.experiment.DatabaseResultListener
  Determines if there are any constraints (imposed by the destination) on any additional measures produced by resultProducers.
determineColumnConstraints(ResultProducer) - Method in class weka.experiment.LearningRateResultProducer
  Determines if there are any constraints (imposed by the destination) on the result columns to be produced by resultProducers.
determineColumnConstraints(ResultProducer) - Method in interface weka.experiment.ResultListener
  Determines if there are any constraints (imposed by the destination) on additional result columns to be produced by resultProducers.
DIAMOND_SHAPE - Static variable in class weka.gui.visualize.Plot2D
differencesProbability - Variable in class weka.experiment.PairedStats
  The probability of obtaining the observed differences
differencesSignificance - Variable in class weka.experiment.PairedStats
  A significance indicator: 0 if the differences are not significant > 0 if x significantly greater than y < 0 if x significantly less than y
differencesStats - Variable in class weka.experiment.PairedStats
  The stats associated with the paired differences
DIRECTED - Static variable in interface weka.gui.graphvisualizer.GraphConstants
  Types of Edges
directionTipText() - Method in class weka.attributeSelection.BestFirst
  Returns the tip text for this property
disabled_getEquivalent() - Method in class weka.associations.Tertius
  Get the value of equivalent.
disabled_getPartFile() - Method in class weka.associations.Tertius
  Get the value of partFile.
disabled_getSameClause() - Method in class weka.associations.Tertius
  Get the value of sameClause.
disabled_getSubsumption() - Method in class weka.associations.Tertius
  Get the value of subsumption.
disabled_setEquivalent(boolean) - Method in class weka.associations.Tertius
  Set the value of equivalent.
disabled_setPartFile(File) - Method in class weka.associations.Tertius
  Set the value of partFile.
disabled_setSameClause(boolean) - Method in class weka.associations.Tertius
  Set the value of sameClause.
disabled_setSubsumption(boolean) - Method in class weka.associations.Tertius
  Set the value of subsumption.
disconnect(NeuralConnection, NeuralConnection) - Static method in class weka.classifiers.functions.neural.NeuralConnection
  Disconnects two units.
disconnectFromDatabase() - Method in class weka.experiment.DatabaseUtils
  Closes the connection to the database.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.AbstractDataSink
  Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.AbstractEvaluator
  Notify this object that it has been deregistered as a listener with a source with respect to the supplied event named
disconnectionNotification(String, Object) - Method in class weka.gui.beans.AbstractTestSetProducer
  Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer
  Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.AbstractTrainingSetProducer
  Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in interface weka.gui.beans.BeanCommon
  Notify this object that it has been deregistered as a listener with a source for named event.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.ClassAssigner
  Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.Classifier
  Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.ClassValuePicker
  Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.Clusterer
  Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.Filter
  Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.MetaBean
  Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.PredictionAppender
  Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.StripChart
  Notify this object that it has been deregistered as a listener with a source for named event.
DiscreteEstimator - Class in weka.estimators
  Simple symbolic probability estimator based on symbol counts.
DiscreteEstimator(int, boolean) - Constructor for class weka.estimators.DiscreteEstimator
  Constructor
DiscreteEstimator(int, double) - Constructor for class weka.estimators.DiscreteEstimator
  Constructor
DiscreteEstimatorBayes - Class in weka.classifiers.bayes.net.estimate
  Symbolic probability estimator based on symbol counts and a prior.
DiscreteEstimatorBayes(int, double) - Constructor for class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes
  Constructor
DiscreteEstimatorFullBayes - Class in weka.classifiers.bayes.net.estimate
  Symbolic probability estimator based on symbol counts and a prior.
DiscreteEstimatorFullBayes(int, double, double, DiscreteEstimatorBayes, DiscreteEstimatorBayes, double) - Constructor for class weka.classifiers.bayes.net.estimate.DiscreteEstimatorFullBayes
  Constructor
DiscreteFunction - Class in weka.classifiers.functions.pace
  Class for handling discrete functions.
DiscreteFunction() - Constructor for class weka.classifiers.functions.pace.DiscreteFunction
  Constructs an empty discrete function
DiscreteFunction(DoubleVector) - Constructor for class weka.classifiers.functions.pace.DiscreteFunction
  Constructs a discrete function with the point values provides and the function values are all 1/n.
DiscreteFunction(DoubleVector, DoubleVector) - Constructor for class weka.classifiers.functions.pace.DiscreteFunction
  Constructs a discrete function with both the point values and function values provided.
Discretize - Class in weka.filters.supervised.attribute
  An instance filter that discretizes a range of numeric attributes in the dataset into nominal attributes.
Discretize() - Constructor for class weka.filters.supervised.attribute.Discretize
  Constructor - initialises the filter
Discretize - Class in weka.filters.unsupervised.attribute
  An instance filter that discretizes a range of numeric attributes in the dataset into nominal attributes.
Discretize() - Constructor for class weka.filters.unsupervised.attribute.Discretize
  Constructor - initialises the filter
Discretize(String) - Constructor for class weka.filters.unsupervised.attribute.Discretize
  Another constructor
displayResultset(int) - Method in class weka.experiment.PairedTTester
  Checks whether the resultset with the given index shall be displayed.
displayRulesTipText() - Method in class weka.classifiers.rules.DecisionTable
  Returns the tip text for this property
dispose() - Method in class weka.gui.visualize.PostscriptGraphics
  Not implemented
disposeSplash() - Static method in class weka.gui.SplashWindow
  Closes the splash window.
distanceWeightingTipText() - Method in class weka.classifiers.lazy.IBk
  Returns the tip text for this property
distinctCount - Variable in class weka.core.AttributeStats
  The number of distinct values
distributedExperimentSelected() - Method in class weka.gui.experiment.DistributeExperimentPanel
  Returns true if the distribute experiment checkbox is selected
DistributeExperimentPanel - Class in weka.gui.experiment
  This panel enables an experiment to be distributed to multiple hosts; it also allows remote host names to be specified.
DistributeExperimentPanel() - Constructor for class weka.gui.experiment.DistributeExperimentPanel
  Constructor
DistributeExperimentPanel(Experiment) - Constructor for class weka.gui.experiment.DistributeExperimentPanel
  Creates the panel with the supplied initial experiment.
distribution() - Method in class weka.classifiers.evaluation.NominalPrediction
  Gets the predicted probabilities
distribution() - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
  Returns the distribution of class values induced by the model.
Distribution - Class in weka.classifiers.trees.j48
  Class for handling a distribution of class values.
Distribution(int, int) - Constructor for class weka.classifiers.trees.j48.Distribution
  Creates and initializes a new distribution.
Distribution(double[][]) - Constructor for class weka.classifiers.trees.j48.Distribution
  Creates and initializes a new distribution using the given array.
Distribution(Instances) - Constructor for class weka.classifiers.trees.j48.Distribution
  Creates a distribution with only one bag according to instances in source.
Distribution(Instances, ClassifierSplitModel) - Constructor for class weka.classifiers.trees.j48.Distribution
  Creates a distribution according to given instances and split model.
Distribution(Distribution) - Constructor for class weka.classifiers.trees.j48.Distribution
  Creates distribution with only one bag by merging all bags of given distribution.
Distribution(Distribution, int) - Constructor for class weka.classifiers.trees.j48.Distribution
  Creates distribution with two bags by merging all bags apart of the indicated one.
distributionForInstance(Instance) - Method in class weka.classifiers.bayes.AODE
  Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.bayes.BayesNet
  Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.bayes.NaiveBayes
  Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.bayes.NaiveBayesMultinomial
  Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.bayes.NaiveBayesSimple
  Calculates the class membership probabilities for the given test instance.
distributionForInstance(BayesNet, Instance) - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator
  Calculates the class membership probabilities for the given test instance.
distributionForInstance(BayesNet, Instance) - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator
  Calculates the class membership probabilities for the given test instance.
distributionForInstance(BayesNet, Instance) - Method in class weka.classifiers.bayes.net.estimate.SimpleEstimator
  Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.Classifier
  Predicts the class memberships for a given instance.
distributionForInstance(Instance) - Method in class weka.classifiers.functions.Logistic
  Computes the distribution for a given instance
distributionForInstance(Instance) - Method in class weka.classifiers.functions.MultilayerPerceptron
  Call this function to predict the class of an instance once a classification model has been built with the buildClassifier call.
distributionForInstance(Instance) - Method in class weka.classifiers.functions.RBFNetwork
  Computes the distribution for a given instance
distributionForInstance(Instance) - Method in class weka.classifiers.functions.SimpleLogistic
  Returns class probabilities for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.functions.SMO
  Estimates class probabilities for given instance.
distributionForInstance(Instance) - Method in class weka.classifiers.functions.VotedPerceptron
  Outputs the distribution for the given output.
distributionForInstance(Instance) - Method in class weka.classifiers.lazy.IBk
  Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.lazy.KStar
  Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.lazy.LBR
  Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.lazy.LWL
  Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.AdaBoostM1
  Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.AttributeSelectedClassifier
  Classifies a given instance after attribute selection
distributionForInstance(Instance) - Method in class weka.classifiers.meta.Bagging
  Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.ClassificationViaRegression
  Returns the distribution for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.CostSensitiveClassifier
  Returns class probabilities.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.CVParameterSelection
  Predicts the class distribution for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.Decorate
  Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.FilteredClassifier
  Classifies a given instance after filtering.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.Grading
  Returns class probabilities for a given instance using the stacked classifier.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.LogitBoost
  Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.MetaCost
  Classifies a given instance after filtering.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.MultiClassClassifier
  Returns the distribution for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.MultiScheme
  Returns class probabilities.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.OrdinalClassClassifier
  Returns the distribution for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost
  Computes class distribution of an instance using the best committee.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.RandomCommittee
  Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.Stacking
  Returns class probabilities.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.StackingC
  Classifies a given instance using the stacked classifier.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.ThresholdSelector
  Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.Vote
  Classifies a given instance using the selected classifier.
distributionForInstance(Instance) - Method in class weka.classifiers.misc.HyperPipes
  Classifies the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.misc.VFI
  Classifies the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.rules.ConjunctiveRule
  Computes class distribution for the given instance.
distributionForInstance(Instance) - Method in class weka.classifiers.rules.DecisionTable
  Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.rules.JRip
  Classify the test instance with the rule learner and provide the class distributions
distributionForInstance(Instance) - Method in class weka.classifiers.rules.part.ClassifierDecList
  Returns class probabilities for a weighted instance.
distributionForInstance(Instance) - Method in class weka.classifiers.rules.PART
  Returns class probabilities for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.rules.part.MakeDecList
  Returns the class distribution for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.rules.ZeroR
  Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.ADTree
  Returns the class probability distribution for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.DecisionStump
  Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.Id3
  Computes class distribution for instance using decision tree.
distributionForInstance(Instance, boolean) - Method in class weka.classifiers.trees.j48.ClassifierTree
  Returns class probabilities for a weighted instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.J48
  Returns class probabilities for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.LMT
  Returns class probabilities for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.lmt.LMTNode
  Returns the class probabilities for an instance given by the logistic model tree.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.lmt.LogisticBase
  Returns class probabilities for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.NBTree
  Returns class probabilities for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.RandomForest
  Returns the class probability distribution for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.RandomTree
  Computes class distribution of an instance using the decision tree.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.REPTree
  Computes class distribution of an instance using the tree.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.UserClassifier
  Call this function to get a double array filled with the probability of how likely each class type is the class of the instance.
distributionForInstance(Instance) - Method in class weka.clusterers.Clusterer
  Predicts the cluster memberships for a given instance.
distributionForInstance(Instance) - Method in class weka.clusterers.DensityBasedClusterer
  Returns the cluster probability distribution for an instance.
distributionsByOriginalIndex(double[]) - Method in class weka.filters.supervised.attribute.ClassOrder
  Convert the given class distribution back to the distributions with the original internal class index
distributionSpreadTipText() - Method in class weka.filters.supervised.instance.SpreadSubsample
  Returns the tip text for this property
distributionTipText() - Method in class weka.filters.unsupervised.attribute.RandomProjection
  Returns the tip text for this property
divergence(BayesNet) - Method in class weka.classifiers.bayes.net.BIFReader
  calculates the divergence between the probability distribution represented by this network and that of another, that is, \sum_{x\in X} P(x)log P(x)/Q(x) where X is the set of values the nodes in the network can take, P(x) the probability of this network for configuration x Q(x) the probability of the other network for configuration x
divide(Instances, boolean) - Static method in class weka.associations.LabeledItemSet
  Splits the class attribute away.
dividedBy(DoubleVector) - Method in class weka.classifiers.functions.pace.DoubleVector
  Divided by another DoubleVector element by element
dividedByEquals(DoubleVector) - Method in class weka.classifiers.functions.pace.DoubleVector
  Divided by another DoubleVector element by element in place
DKConditionalEstimator - Class in weka.estimators
  Conditional probability estimator for a discrete domain conditional upon a numeric domain.
DKConditionalEstimator(int, double) - Constructor for class weka.estimators.DKConditionalEstimator
  Constructor
DNConditionalEstimator - Class in weka.estimators
  Conditional probability estimator for a discrete domain conditional upon a numeric domain.
DNConditionalEstimator(int, double) - Constructor for class weka.estimators.DNConditionalEstimator
  Constructor
dnorm(double) - Static method in class weka.classifiers.functions.pace.Maths
  Returns the density of the standard normal.
dnorm(double, double, double) - Static method in class weka.classifiers.functions.pace.Maths
  Returns the density value of a standard normal.
dnorm(double, DoubleVector, double) - Static method in class weka.classifiers.functions.pace.Maths
  Returns the density values of a set of normal distributions with different means.
dnormLog(double) - Static method in class weka.classifiers.functions.pace.Maths
  Returns the log-density of the standard normal.
dnormLog(double, double, double) - Static method in class weka.classifiers.functions.pace.Maths
  Returns the log-density value of a standard normal.
dnormLog(double, DoubleVector, double) - Static method in class weka.classifiers.functions.pace.Maths
  Returns the log-density values of a set of normal distributions with different means.
DOCTYPE - Static variable in class weka.core.xml.XMLOptions
  the DTD for the XML file
DOCTYPE - Static variable in class weka.core.xml.XMLSerialization
  the DOCTYPE for the serialization
doHistory(KeyEvent) - Method in class weka.gui.SimpleCLI
  Changes the currently displayed command line when certain keys are pressed.
doMetaConnection(BeanInstance, BeanInstance, EventSetDescriptor, JComponent) - Static method in class weka.gui.beans.BeanConnection
done() - Method in interface weka.classifiers.IterativeClassifier
  Signal end of iterating, useful for any house-keeping/cleanup
done() - Method in class weka.classifiers.trees.ADTree
  Frees memory that is no longer needed for a final model - will no longer be able to increment the classifier after calling this.
dontNormalizeTipText() - Method in class weka.classifiers.lazy.LWL
  Returns the tip text for this property
doRun(int) - Method in class weka.experiment.AveragingResultProducer
  Gets the results for a specified run number.
doRun(int) - Method in class weka.experiment.CrossValidationResultProducer
  Gets the results for a specified run number.
doRun(int) - Method in class weka.experiment.DatabaseResultProducer
  Gets the results for a specified run number.
doRun(int) - Method in class weka.experiment.LearningRateResultProducer
  Gets the results for a specified run number.
doRun(int) - Method in class weka.experiment.RandomSplitResultProducer
  Gets the results for a specified run number.
doRun(int) - Method in interface weka.experiment.ResultProducer
  Gets the results for a specified run number.
doRunKeys(int) - Method in class weka.experiment.AveragingResultProducer
  Gets the keys for a specified run number.
doRunKeys(int) - Method in class weka.experiment.CrossValidationResultProducer
  Gets the keys for a specified run number.
doRunKeys(int) - Method in class weka.experiment.DatabaseResultProducer
  Gets the keys for a specified run number.
doRunKeys(int) - Method in class weka.experiment.LearningRateResultProducer
  Gets the keys for a specified run number.
doRunKeys(int) - Method in class weka.experiment.RandomSplitResultProducer
  Gets the keys for a specified run number.
doRunKeys(int) - Method in interface weka.experiment.ResultProducer
  Gets the keys for a specified run number.
doTests() - Method in class weka.classifiers.CheckClassifier
  Begin the tests, reporting results to System.out
DotParser - Class in weka.gui.graphvisualizer
  This class parses input in DOT format, and builds the datastructures that are passed to it.
DotParser(Reader, FastVector, FastVector) - Constructor for class weka.gui.graphvisualizer.DotParser
  Dot parser Constructor
DOUBLE - Static variable in class weka.core.converters.DatabaseLoader
DOUBLE - Static variable in class weka.experiment.DatabaseUtils
  Type mapping for DOUBLE used for reading experiment results
DOUBLE - Static variable in interface weka.gui.graphvisualizer.GraphConstants
  Types of Edges
doubleToString(double, int) - Static method in class weka.core.Utils
  Rounds a double and converts it into String.
doubleToString(double, int, int) - Static method in class weka.core.Utils
  Rounds a double and converts it into a formatted decimal-justified String.
DoubleVector - Class in weka.classifiers.functions.pace
DoubleVector() - Constructor for class weka.classifiers.functions.pace.DoubleVector
  Constructs a null vector.
DoubleVector(int) - Constructor for class weka.classifiers.functions.pace.DoubleVector
  Constructs an n-vector of zeros.
DoubleVector(int, double) - Constructor for class weka.classifiers.functions.pace.DoubleVector
  Constructs a constant n-vector.
DoubleVector(double[]) - Constructor for class weka.classifiers.functions.pace.DoubleVector
  Constructs a vector directly from a double array
draw(Shape) - Method in class weka.gui.visualize.PostscriptGraphics
draw3DRect(int, int, int, int, boolean) - Method in class weka.gui.visualize.PostscriptGraphics
  Draw an outlined rectangle with 3D effect in current pen color.
Drawable - Interface in weka.core
  Interface to something that can be drawn as a graph.
drawArc(int, int, int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
  Not implemented
drawBytes(byte[], int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
  simply calls drawString(String,int,int)
drawChars(char[], int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
  simply calls drawString(String,int,int)
drawGlyphVector(GlyphVector, float, float) - Method in class weka.gui.visualize.PostscriptGraphics
drawHighlight(Graphics, int, int) - Method in class weka.classifiers.functions.neural.NeuralConnection
  Call this function to draw the node highlighted.
drawImage(Image, int, int, Color, ImageObserver) - Method in class weka.gui.visualize.PostscriptGraphics
  calls drawImage(Image,int,int,int,int,Color,ImageObserver)
drawImage(Image, int, int, ImageObserver) - Method in class weka.gui.visualize.PostscriptGraphics
  calls drawImage(Image,int,int,Color,ImageObserver) with Color.WHITE as background color
drawImage(Image, int, int, int, int, Color, ImageObserver) - Method in class weka.gui.visualize.PostscriptGraphics
  PS see http://astronomy.swin.edu.au/~pbourke/geomformats/postscript/ Java http://show.docjava.com:8086/book/cgij/doc/ip/graphics/SimpleImageFrame.java.html
drawImage(Image, int, int, int, int, ImageObserver) - Method in class weka.gui.visualize.PostscriptGraphics
  calls drawImage(Image,int,int,int,int,Color,ImageObserver) with the color WHITE as background
drawImage(Image, int, int, int, int, int, int, int, int, Color, ImageObserver) - Method in class weka.gui.visualize.PostscriptGraphics
  Not implemented
drawImage(Image, int, int, int, int, int, int, int, int, ImageObserver) - Method in class weka.gui.visualize.PostscriptGraphics
  calls drawImage(Image,int,int,int,int,int,int,int,int,Color,ImageObserver) with Color.WHITE as background color
drawImage(BufferedImage, BufferedImageOp, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
drawImage(Image, AffineTransform, ImageObserver) - Method in class weka.gui.visualize.PostscriptGraphics
drawInputLines(Graphics, int, int) - Method in class weka.classifiers.functions.neural.NeuralConnection
  Call this function to draw the nodes input connections.
drawLine(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
  Draw a line in current pen color.
drawNode(Graphics, int, int) - Method in class weka.classifiers.functions.neural.NeuralConnection
  Call this function to draw the node.
drawOutputLines(Graphics, int, int) - Method in class weka.classifiers.functions.neural.NeuralConnection
  Call this function to draw the nodes output connections.
drawOval(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
  Draw an Oval outline in current pen color.
drawPolygon(int[], int[], int) - Method in class weka.gui.visualize.PostscriptGraphics
  Not implemented
drawPolyline(int[], int[], int) - Method in class weka.gui.visualize.PostscriptGraphics
  Not implemented
drawRect(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
  Draw an outlined rectangle in current pen color.
drawRenderableImage(RenderableImage, AffineTransform) - Method in class weka.gui.visualize.PostscriptGraphics
drawRenderedImage(RenderedImage, AffineTransform) - Method in class weka.gui.visualize.PostscriptGraphics
drawRoundRect(int, int, int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
  Not implemented
drawString(AttributedCharacterIterator, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
  Not implemented
drawString(String, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
  Draw text in current pen color.
drawString(AttributedCharacterIterator, float, float) - Method in class weka.gui.visualize.PostscriptGraphics
drawString(String, float, float) - Method in class weka.gui.visualize.PostscriptGraphics
dumpDistribution() - Method in class weka.classifiers.trees.j48.Distribution
  Prints distribution.
dumpLabel(int, Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
  Prints label for subset index of instances (eg class).
dumpModel(Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
  Prints the split model.

## E

EAST_CONNECTOR - Static variable in class weka.gui.beans.BeanVisual
Edge - Class in weka.gui.treevisualizer
  This class is used in conjunction with the Node class to form a tree structure.
Edge(String, String, String) - Constructor for class weka.gui.treevisualizer.Edge
  This constructs an Edge with the specified label and parent , child serial tags.
edit() - Method in class weka.gui.explorer.PreprocessPanel
  edits the current instances object in the viewer
editableProperties() - Method in class weka.gui.PropertySheetPanel
  Gets the number of editable properties for the current target.
eig() - Method in class weka.core.matrix.Matrix
  Eigenvalue Decomposition
EigenvalueDecomposition - Class in weka.core.matrix
  Eigenvalues and eigenvectors of a real matrix.
eigenvalueDecomposition(double[][], double[]) - Method in class weka.core.Matrix
  Deprecated. Performs Eigenvalue Decomposition using Householder QR Factorization Matrix must be symmetrical.
EigenvalueDecomposition(Matrix) - Constructor for class weka.core.matrix.EigenvalueDecomposition
  Check for symmetry, then construct the eigenvalue decomposition
elementAt(int) - Method in class weka.core.FastVector
  Returns the element at the given position.
elements() - Method in class weka.core.FastVector
  Returns an enumeration of this vector.
elements(int) - Method in class weka.core.FastVector
  Returns an enumeration of this vector, skipping the element with the given index.
eliminateColinearAttributesTipText() - Method in class weka.classifiers.functions.LinearRegression
  Returns the tip text for this property
EM - Class in weka.clusterers
  Simple EM (expectation maximisation) class.
EM() - Constructor for class weka.clusterers.EM
  Constructor.
empiricalBayesEstimate(double) - Method in class weka.classifiers.functions.pace.NormalMixture
  Returns the empirical Bayes estimate of a single value.
empiricalBayesEstimate(DoubleVector) - Method in class weka.classifiers.functions.pace.NormalMixture
  Returns the empirical Bayes estimate of a vector.
empiricalProbability(DoubleVector, PaceMatrix) - Method in class weka.classifiers.functions.pace.MixtureDistribution
  Computes the empirical probabilities of the data over a set of intervals.
empty() - Method in class weka.core.Queue
  Checks if queue is empty.
entropicAutoBlendTipText() - Method in class weka.classifiers.lazy.KStar
  Returns the tip text for this property
ENTROPY - Static variable in interface weka.classifiers.bayes.net.search.local.Scoreable
entropy(double[]) - Static method in class weka.core.ContingencyTables
  Computes the entropy of the given array.
EntropyBasedSplitCrit - Class in weka.classifiers.trees.j48
  "Abstract" class for computing splitting criteria based on the entropy of a class distribution.
EntropyBasedSplitCrit() - Constructor for class weka.classifiers.trees.j48.EntropyBasedSplitCrit
entropyConditionedOnColumns(double[][]) - Static method in class weka.core.ContingencyTables
  Computes conditional entropy of the rows given the columns.
entropyConditionedOnRows(double[][]) - Static method in class weka.core.ContingencyTables
  Computes conditional entropy of the columns given the rows.
entropyConditionedOnRows(double[][], double[][], double) - Static method in class weka.core.ContingencyTables
  Computes conditional entropy of the columns given the rows of the test matrix with respect to the train matrix.
entropyGain() - Method in class weka.classifiers.trees.lmt.ResidualSplit
  Computes entropy gain for current split.
entropyOverColumns(double[][]) - Static method in class weka.core.ContingencyTables
  Computes the columns' entropy for the given contingency table.
entropyOverRows(double[][]) - Static method in class weka.core.ContingencyTables
  Computes the rows' entropy for the given contingency table.
EntropySplitCrit - Class in weka.classifiers.trees.j48
  Class for computing the entropy for a given distribution.
EntropySplitCrit() - Constructor for class weka.classifiers.trees.j48.EntropySplitCrit
enumerateAttributes() - Method in class weka.core.Instance
  Returns an enumeration of all the attributes.
enumerateAttributes() - Method in class weka.core.Instances
  Returns an enumeration of all the attributes.
enumerateInstances() - Method in class weka.core.Instances
  Returns an enumeration of all instances in the dataset.
enumerateLiterals() - Method in class weka.associations.tertius.LiteralSet
  Enumerate the literals contained in this set.
enumerateMeasures() - Method in class weka.classifiers.bayes.BayesNet
  Returns an enumeration of the measure names.
enumerateMeasures() - Method in class weka.classifiers.functions.SimpleLogistic
  Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.meta.AdditiveRegression
  Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.meta.AttributeSelectedClassifier
  Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.meta.Bagging
  Returns an enumeration of the additional measure names.
enumerateMeasures() - Method in class weka.classifiers.rules.DecisionTable
  Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.rules.JRip
  Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.rules.PART
  Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.rules.Ridor
  Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.trees.ADTree
  Returns an enumeration of the additional measure names.
enumerateMeasures() - Method in class weka.classifiers.trees.J48
  Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.trees.LMT
  Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.trees.m5.M5Base
  Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.trees.NBTree
  Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.trees.RandomForest
  Returns an enumeration of the additional measure names.
enumerateMeasures() - Method in class weka.classifiers.trees.REPTree
  Returns an enumeration of the additional measure names.
enumerateMeasures() - Method in interface weka.core.AdditionalMeasureProducer
  Returns an enumeration of the measure names.
enumerateMeasures() - Method in class weka.experiment.AveragingResultProducer
  Returns an enumeration of any additional measure names that might be in the result producer
enumerateMeasures() - Method in class weka.experiment.ClassifierSplitEvaluator
  Returns an enumeration of any additional measure names that might be in the classifier
enumerateMeasures() - Method in class weka.experiment.CrossValidationResultProducer
  Returns an enumeration of any additional measure names that might be in the SplitEvaluator
enumerateMeasures() - Method in class weka.experiment.DatabaseResultProducer
  Returns an enumeration of any additional measure names that might be in the result producer
enumerateMeasures() - Method in class weka.experiment.LearningRateResultProducer
  Returns an enumeration of any additional measure names that might be in the result producer
enumerateMeasures() - Method in class weka.experiment.RandomSplitResultProducer
  Returns an enumeration of any additional measure names that might be in the SplitEvaluator
enumerateMeasures() - Method in class weka.experiment.RegressionSplitEvaluator
  Returns an enumeration of any additional measure names that might be in the classifier
enumerateRequests() - Method in class weka.gui.beans.AttributeSummarizer
  Return an enumeration of actions that the user can ask this bean to perform
enumerateRequests() - Method in class weka.gui.beans.Classifier
  Return an enumeration of requests that can be made by the user
enumerateRequests() - Method in class weka.gui.beans.ClassifierPerformanceEvaluator
  Return an enumeration of user activated requests for this bean
enumerateRequests() - Method in class weka.gui.beans.Clusterer
  Return an enumeration of requests that can be made by the user
enumerateRequests() - Method in class weka.gui.beans.ClustererPerformanceEvaluator
  Return an enumeration of user activated requests for this bean
enumerateRequests() - Method in class weka.gui.beans.CrossValidationFoldMaker
  Return an enumeration of user requests
enumerateRequests() - Method in class weka.gui.beans.DataVisualizer
  Describe `enumerateRequests` method here.
enumerateRequests() - Method in class weka.gui.beans.Filter
  Return an enumeration of user requests
enumerateRequests() - Method in class weka.gui.beans.GraphViewer
  Return an enumeration of user requests
enumerateRequests() - Method in class weka.gui.beans.Loader
  Get a list of user requests
enumerateRequests() - Method in class weka.gui.beans.MetaBean
  Return an enumeration of requests that can be made by the user
enumerateRequests() - Method in class weka.gui.beans.ModelPerformanceChart
  Describe `enumerateRequests` method here.
enumerateRequests() - Method in class weka.gui.beans.StripChart
  Describe `enumerateRequests` method here.
enumerateRequests() - Method in class weka.gui.beans.TextViewer
  Get a list of user requests
enumerateRequests() - Method in class weka.gui.beans.TrainTestSplitMaker
  Get list of user requests
enumerateRequests() - Method in interface weka.gui.beans.UserRequestAcceptor
  Get a list of performable requests
enumerateValues() - Method in class weka.core.Attribute
  Returns an enumeration of all the attribute's values if the attribute is nominal or a string, null otherwise.
EPSILON - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
epsilonParameterTipText() - Method in class weka.attributeSelection.SVMAttributeEval
  Returns a tip text for this property suitable for display in the GUI
epsilonTipText() - Method in class weka.classifiers.functions.SMO
  Returns the tip text for this property
epsilonTipText() - Method in class weka.classifiers.functions.SMOreg
  Returns the tip text for this property
epsTipText() - Method in class weka.classifiers.functions.SMOreg
  Returns the tip text for this property
eq(double, double) - Static method in class weka.core.Utils
  Tests if a is equal to b.
equalCondset(Object) - Method in class weka.associations.LabeledItemSet
  Compares two item sets
equalHeaders(Instance) - Method in class weka.core.Instance
  Tests if the headers of two instances are equivalent.
equalHeaders(Instances) - Method in class weka.core.Instances
  Checks if two headers are equivalent.
equals(Object) - Method in class weka.associations.ItemSet
  Tests if two item sets are equal.
equals(Object) - Method in class weka.associations.LabeledItemSet
  Tests if two item sets are equal.
equals(Object) - Method in class weka.associations.RuleItem
  returns whether two RuleItems are equal
equals(Object) - Method in class weka.attributeSelection.ConsistencySubsetEval.hashKey
  Tests if two instances are equal
equals(Object) - Method in class weka.classifiers.Evaluation
  Tests whether the current evaluation object is equal to another evaluation object
equals(Object) - Method in class weka.classifiers.rules.DecisionTable.hashKey
  Tests if two instances are equal
equals(Object) - Method in class weka.core.Attribute
  Tests if given attribute is equal to this attribute.
equals(Object) - Method in class weka.core.RTSI.StringCompare
  Indicates whether some other object is "equal to" this Comparator.
equals(Object) - Method in class weka.core.SelectedTag
  Returns true if this SelectedTag equals another object
equals(Object) - Method in class weka.core.SerializedObject
equals(Object) - Method in class weka.core.Version
  whether the given version string is equal to this version
equals(Object) - Method in class weka.gui.graphvisualizer.GraphEdge
equals(Object) - Method in class weka.gui.graphvisualizer.GraphNode
  Returns true if passed in argument is an instance of GraphNode and is equal to this node.
equalTo(Splitter) - Method in class weka.classifiers.trees.adtree.Splitter
  Tests whether two splitters are equivalent.
equalTo(Splitter) - Method in class weka.classifiers.trees.adtree.TwoWayNominalSplit
  Tests whether two splitters are equivalent.
equalTo(Splitter) - Method in class weka.classifiers.trees.adtree.TwoWayNumericSplit
  Tests whether two splitters are equivalent.
equalTo(Test) - Method in class weka.datagenerators.Test
  Compares the test with the test that is given as parameter.
equivalentTipText() - Method in class weka.associations.Tertius
  Returns the tip text for this property.
equivalentTo(Rule) - Method in class weka.associations.tertius.Rule
  Test if this rule is equivalent to another rule.
errms(StreamTokenizer, String) - Static method in class weka.core.converters.ConverterUtils
  Throws error message with line number and last token read.
error() - Method in class weka.classifiers.evaluation.NumericPrediction
  Calculates the prediction error.
ERROR_SHAPE - Static variable in class weka.gui.visualize.Plot2D
ErrorBasedMeritEvaluator - Interface in weka.attributeSelection
  Interface for evaluators that calculate the "merit" of attributes/subsets as the error of a learning scheme
errorOnProbabilitiesTipText() - Method in class weka.classifiers.functions.SimpleLogistic
  Returns the tip text for this property
errorOnProbabilitiesTipText() - Method in class weka.classifiers.trees.LMT
  Returns the tip text for this property
errorRate() - Method in class weka.classifiers.evaluation.ConfusionMatrix
  Returns the estimated error rate.
errorRate() - Method in class weka.classifiers.Evaluation
  Returns the estimated error rate or the root mean squared error (if the class is numeric).
errorValue(NeuralNode) - Method in class weka.classifiers.functions.neural.LinearUnit
  This function calculates what the error value should be.
errorValue(boolean) - Method in class weka.classifiers.functions.neural.NeuralConnection
  Call this to get the error value of this unit.
errorValue(NeuralNode) - Method in interface weka.classifiers.functions.neural.NeuralMethod
  This function calculates what the error value should be.
errorValue(boolean) - Method in class weka.classifiers.functions.neural.NeuralNode
  Call this to get the error value of this unit.
errorValue(NeuralNode) - Method in class weka.classifiers.functions.neural.SigmoidUnit
  This function calculates what the error value should be.
estimateCPTs() - Method in class weka.classifiers.bayes.BayesNet
  estimateCPTs estimates the conditional probability tables for the Bayes Net using the network structure.
estimateCPTs(BayesNet) - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator
  estimateCPTs estimates the conditional probability tables for the Bayes Net using the network structure.
estimateCPTs(BayesNet) - Method in class weka.classifiers.bayes.net.estimate.BMAEstimator
  estimateCPTs estimates the conditional probability tables for the Bayes Net using the network structure.
estimateCPTs(BayesNet) - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator
  estimateCPTs estimates the conditional probability tables for the Bayes Net using the network structure.
estimateCPTs(BayesNet) - Method in class weka.classifiers.bayes.net.estimate.SimpleEstimator
  estimateCPTs estimates the conditional probability tables for the Bayes Net using the network structure.
estimatePrior() - Method in class weka.associations.PriorEstimation
  Method to estimate the prior probabilities
Estimator - Interface in weka.estimators
  Interface for probability estimators.
estimatorTipText() - Method in class weka.classifiers.bayes.BayesNet
  This will return a string describing the BayesNetEstimator.
estimatorTipText() - Method in class weka.classifiers.functions.PaceRegression
  Returns the tip text for this property
eval(int, int, Instance) - Method in class weka.classifiers.functions.supportVector.CachedKernel
  Implements the abstract function of Kernel using the cache.
eval(int, int, Instance) - Method in class weka.classifiers.functions.supportVector.Kernel
  Computes the result of the kernel function for two instances.
eval(int, int, Instance) - Method in class weka.classifiers.functions.supportVector.NormalizedPolyKernel
  Redefines the eval function of PolyKernel.
EVAL_CROSS_VALIDATION - Static variable in class weka.classifiers.meta.ThresholdSelector
EVAL_TRAINING_SET - Static variable in class weka.classifiers.meta.ThresholdSelector
EVAL_TUNED_SPLIT - Static variable in class weka.classifiers.meta.ThresholdSelector
evaluateAttribute(int) - Method in class weka.attributeSelection.AttributeEvaluator
  evaluates an individual attribute
evaluateAttribute(int) - Method in class weka.attributeSelection.ChiSquaredAttributeEval
  evaluates an individual attribute by measuring its chi-squared value.
evaluateAttribute(int) - Method in class weka.attributeSelection.GainRatioAttributeEval
  evaluates an individual attribute by measuring the gain ratio of the class given the attribute.
evaluateAttribute(int) - Method in class weka.attributeSelection.InfoGainAttributeEval
  evaluates an individual attribute by measuring the amount of information gained about the class given the attribute.
evaluateAttribute(int) - Method in class weka.attributeSelection.OneRAttributeEval
  evaluates an individual attribute by measuring the amount of information gained about the class given the attribute.
evaluateAttribute(int) - Method in class weka.attributeSelection.PrincipalComponents
  Evaluates the merit of a transformed attribute.
evaluateAttribute(int) - Method in class weka.attributeSelection.ReliefFAttributeEval
  Evaluates an individual attribute using ReliefF's instance based approach.
evaluateAttribute(int) - Method in class weka.attributeSelection.SVMAttributeEval
  Evaluates an attribute by returning the rank of the square of its coefficient in a linear support vector machine.
evaluateAttribute(int) - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval
  evaluates an individual attribute by measuring the symmetrical uncertainty between it and the class.
evaluateClusterer(Instances) - Method in class weka.clusterers.ClusterEvaluation
  Evaluate the clusterer on a set of instances.
evaluateClusterer(Clusterer, String[]) - Static method in class weka.clusterers.ClusterEvaluation
  Evaluates a clusterer with the options given in an array of strings.
evaluateModel(String, String[]) - Static method in class weka.classifiers.Evaluation
  Evaluates a classifier with the options given in an array of strings.
evaluateModel(Classifier, String[]) - Static method in class weka.classifiers.Evaluation
  Evaluates a classifier with the options given in an array of strings.
evaluateModel(Classifier, Instances) - Method in class weka.classifiers.Evaluation
  Evaluates the classifier on a given set of instances.
evaluateModelOnce(Classifier, Instance) - Method in class weka.classifiers.Evaluation
  Evaluates the classifier on a single instance.
evaluateModelOnce(double[], Instance) - Method in class weka.classifiers.Evaluation
  Evaluates the supplied distribution on a single instance.
evaluateModelOnce(double, Instance) - Method in class weka.classifiers.Evaluation
  Evaluates the supplied prediction on a single instance.
evaluateSubset(BitSet) - Method in class weka.attributeSelection.CfsSubsetEval
  evaluates a subset of attributes
evaluateSubset(BitSet) - Method in class weka.attributeSelection.ClassifierSubsetEval
  Evaluates a subset of attributes
evaluateSubset(BitSet, Instances) - Method in class weka.attributeSelection.ClassifierSubsetEval
  Evaluates a subset of attributes with respect to a set of instances.
evaluateSubset(BitSet, Instance, boolean) - Method in class weka.attributeSelection.ClassifierSubsetEval
  Evaluates a subset of attributes with respect to a single instance.
evaluateSubset(BitSet) - Method in class weka.attributeSelection.ConsistencySubsetEval
  Evaluates a subset of attributes
evaluateSubset(BitSet, Instances) - Method in class weka.attributeSelection.HoldOutSubsetEvaluator
  Evaluates a subset of attributes with respect to a set of instances.
evaluateSubset(BitSet, Instance, boolean) - Method in class weka.attributeSelection.HoldOutSubsetEvaluator
  Evaluates a subset of attributes with respect to a single instance.
evaluateSubset(BitSet) - Method in class weka.attributeSelection.SubsetEvaluator
  evaluates a subset of attributes
evaluateSubset(BitSet) - Method in class weka.attributeSelection.WrapperSubsetEval
  Evaluates a subset of attributes
Evaluation - Class in weka.classifiers
  Class for evaluating machine learning models.
Evaluation(Instances) - Constructor for class weka.classifiers.Evaluation
  Initializes all the counters for the evaluation.
Evaluation(Instances, CostMatrix) - Constructor for class weka.classifiers.Evaluation
  Initializes all the counters for the evaluation and also takes a cost matrix as parameter.
evaluationModeTipText() - Method in class weka.classifiers.meta.ThresholdSelector
EvaluationUtils - Class in weka.classifiers.evaluation
  Contains utility functions for generating lists of predictions in various manners.
EvaluationUtils() - Constructor for class weka.classifiers.evaluation.EvaluationUtils
evaluatorTipText() - Method in class weka.classifiers.meta.AttributeSelectedClassifier
  Returns the tip text for this property
evaluatorTipText() - Method in class weka.filters.supervised.attribute.AttributeSelection
  Returns the tip text for this property
evalUsingTrainingDataTipText() - Method in class weka.attributeSelection.OneRAttributeEval
  Returns a string for this option suitable for display in the gui as a tip text
EventConstraints - Interface in weka.gui.beans
  Interface for objects that want to be able to specify at any given time whether their current configuration allows a particular event to be generated.
eventGeneratable(String) - Method in class weka.gui.beans.ClassAssigner
  Returns true, if at the current time, the named event could be generated.
eventGeneratable(EventSetDescriptor) - Method in class weka.gui.beans.Classifier
  Returns true, if at the current time, the event described by the supplied event descriptor could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.Classifier
  Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator
  Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.ClassValuePicker
  Returns true, if at the current time, the named event could be generated.
eventGeneratable(EventSetDescriptor) - Method in class weka.gui.beans.Clusterer
  Returns true, if at the current time, the event described by the supplied event descriptor could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.Clusterer
  Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.ClustererPerformanceEvaluator
  Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.CrossValidationFoldMaker
  Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in interface weka.gui.beans.EventConstraints
  Returns true if, at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.Filter
  Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.IncrementalClassifierEvaluator
  Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.Loader
  Returns true if the named event can be generated at this time
eventGeneratable(EventSetDescriptor) - Method in class weka.gui.beans.MetaBean
  Returns true, if at the current time, the event described by the supplied event descriptor could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.MetaBean
  Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.PredictionAppender
  Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.TestSetMaker
  Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.TrainingSetMaker
  Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.TrainTestSplitMaker
  Returns true, if at the current time, the named event could be generated.
exclusiveTipText() - Method in class weka.classifiers.rules.ConjunctiveRule
  Returns the tip text for this property
execute(String) - Method in class weka.experiment.DatabaseUtils
  Executes a SQL query.
execute() - Method in class weka.experiment.RemoteExperimentSubTask
  Run the experiment
execute() - Method in interface weka.experiment.Task
  Execute this task.
execute() - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
  Perform the sub task
execute() - Method in class weka.gui.GenericPropertiesCreator
  generates the props-file for the GenericObjectEditor and stores it
execute(boolean) - Method in class weka.gui.GenericPropertiesCreator
  generates the props-file for the GenericObjectEditor and stores it only if the the param `store` is TRUE.
executeTask(Task) - Method in interface weka.experiment.Compute
  Execute a task
executeTask(Task) - Method in class weka.experiment.RemoteEngine
  Takes a task object and queues it for execution
ExhaustiveSearch - Class in weka.attributeSelection
  Class for performing an exhaustive search.
ExhaustiveSearch() - Constructor for class weka.attributeSelection.ExhaustiveSearch
  Constructor
EXP_INDEX_TABLE - Static variable in class weka.experiment.DatabaseUtils
  The name of the table containing the index to experiments
EXP_RESULT_COL - Static variable in class weka.experiment.DatabaseUtils
  The name of the column containing the results table name
EXP_RESULT_PREFIX - Static variable in class weka.experiment.DatabaseUtils
  The prefix for result table names
EXP_SETUP_COL - Static variable in class weka.experiment.DatabaseUtils
  The name of the column containing the experiment setup (parameters)
EXP_TYPE_COL - Static variable in class weka.experiment.DatabaseUtils
  The name of the column containing the experiment type (ResultProducer)
expectation(double, int, double[], Hashtable) - Static method in class weka.associations.RuleGeneration
  calculates the expected predctive accuracy of a rule
expectedCosts(double[]) - Method in class weka.classifiers.CostMatrix
  Calculates the expected misclassification cost for each possible class value, given class probability estimates.
expectedResultsPerAverageTipText() - Method in class weka.experiment.AveragingResultProducer
  Returns the tip text for this property
Experiment - Class in weka.experiment
  Holds all the necessary configuration information for a standard type experiment.
Experiment() - Constructor for class weka.experiment.Experiment
Experimenter - Class in weka.gui.experiment
  The main class for the experiment environment.
Experimenter(boolean) - Constructor for class weka.gui.experiment.Experimenter
  Creates the experiment environment gui with no initial experiment
ExperimenterDefaults - Class in weka.gui.experiment
  This class offers get methods for the default Experimenter settings in the props file `weka.gui.experiment.Experimenter.props`.
ExperimenterDefaults() - Constructor for class weka.gui.experiment.ExperimenterDefaults
experimentIndexExists() - Method in class weka.experiment.DatabaseUtils
  Returns true if the experiment index exists.
EXPLICIT - Static variable in class weka.associations.Tertius
  Ways of handling missing values.
Explorer - Class in weka.gui.explorer
  The main class for the Weka explorer.
Explorer() - Constructor for class weka.gui.explorer.Explorer
  Creates the experiment environment gui with no initial experiment
ExponentialFormat - Class in weka.classifiers.functions.pace
ExponentialFormat() - Constructor for class weka.classifiers.functions.pace.ExponentialFormat
ExponentialFormat(int) - Constructor for class weka.classifiers.functions.pace.ExponentialFormat
ExponentialFormat(int, boolean) - Constructor for class weka.classifiers.functions.pace.ExponentialFormat
ExponentialFormat(int, int, boolean, boolean) - Constructor for class weka.classifiers.functions.pace.ExponentialFormat
exponentTipText() - Method in class weka.classifiers.functions.SMO
  Returns the tip text for this property
exponentTipText() - Method in class weka.classifiers.functions.SMOreg
  Returns the tip text for this property
exponentTipText() - Method in class weka.classifiers.functions.VotedPerceptron
  Returns the tip text for this property
expressionTipText() - Method in class weka.filters.unsupervised.attribute.AddExpression
  Returns the tip text for this property
ExtensionFileFilter - Class in weka.gui
  Provides a file filter for FileChoosers that accepts or rejects files based on their extension.
ExtensionFileFilter(String, String) - Constructor for class weka.gui.ExtensionFileFilter
  Creates the ExtensionFileFilter
ExtensionFileFilter(String[], String) - Constructor for class weka.gui.ExtensionFileFilter
  Creates an ExtensionFileFilter that accepts files that have any of the extensions contained in the supplied array.
extraArcs(BayesNet) - Method in class weka.classifiers.bayes.net.BIFReader
  Count nr of exta arcs from other network compared to current network Note that an arc is not 'extra' if it is reversed.

## F

f(double) - Method in class weka.classifiers.functions.pace.ChisqMixture
  Computes the value of f(x) given the mixture.
f(DoubleVector) - Method in class weka.classifiers.functions.pace.ChisqMixture
  Computes the value of f(x) given the mixture, where x is a vector.
f(double) - Method in class weka.classifiers.functions.pace.NormalMixture
  Computes the value of f(x) given the mixture.
f(DoubleVector) - Method in class weka.classifiers.functions.pace.NormalMixture
  Computes the value of f(x) given the mixture, where x is a vector.
FAILED - Static variable in class weka.experiment.TaskStatusInfo
FALLOUT_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve
FALSE_NEG_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve
FALSE_POS_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve
falseNegativeRate(int) - Method in class weka.classifiers.Evaluation
  Calculate the false negative rate with respect to a particular class.
falsePositiveRate(int) - Method in class weka.classifiers.Evaluation
  Calculate the false positive rate with respect to a particular class.
FarthestFirst - Class in weka.clusterers
  Implements the "Farthest First Traversal Algorithm" by Hochbaum and Shmoys 1985: A best possible heuristic for the k-center problem, Mathematics of Operations Research, 10(2):180-184, as cited by Sanjoy Dasgupta "performance guarantees for hierarchical clustering", colt 2002, sydney works as a fast simple approximate clusterer modelled after SimpleKMeans, might be a useful initializer for it Valid options are:
FarthestFirst() - Constructor for class weka.clusterers.FarthestFirst
fastRegressionTipText() - Method in class weka.classifiers.trees.LMT
  Returns the tip text for this property
FastVector - Class in weka.core
  Implements a fast vector class without synchronized methods.
FastVector() - Constructor for class weka.core.FastVector
  Constructs an empty vector with initial capacity zero.
FastVector(int) - Constructor for class weka.core.FastVector
  Constructs a vector with the given capacity.
FastVector.FastVectorEnumeration - Class in weka.core
  Class for enumerating the vector's elements.
FastVector.FastVectorEnumeration(FastVector) - Constructor for class weka.core.FastVector.FastVectorEnumeration
  Constructs an enumeration.
FastVector.FastVectorEnumeration(FastVector, int) - Constructor for class weka.core.FastVector.FastVectorEnumeration
  Constructs an enumeration with a special element.
featureSpaceNormalizationTipText() - Method in class weka.classifiers.functions.SMO
  Returns the tip text for this property
featureSpaceNormalizationTipText() - Method in class weka.classifiers.functions.SMOreg
  Returns the tip text for this property
FILE_EXTENSION - Static variable in class weka.classifiers.CostMatrix
  The deafult file extension for cost matrix files
FILE_EXTENSION - Static variable in class weka.core.converters.ArffLoader
FILE_EXTENSION - Static variable in class weka.core.converters.C45Loader
FILE_EXTENSION - Static variable in class weka.core.converters.CSVLoader
FILE_EXTENSION - Static variable in class weka.core.converters.SerializedInstancesLoader
FILE_EXTENSION - Static variable in class weka.core.Instances
  The filename extension that should be used for arff files
FILE_EXTENSION - Static variable in class weka.core.xml.KOML
  the extension for KOML files (including '.')
FILE_EXTENSION - Static variable in class weka.experiment.Experiment
  The filename extension that should be used for experiment files
FILE_EXTENSION - Static variable in class weka.gui.beans.KnowledgeFlowApp
  the extension for the serialized setups (Java serialization)
FILE_EXTENSION_XML - Static variable in class weka.gui.beans.KnowledgeFlowApp
  the extension for the serialized setups (Java serialization)
FileChooser - Class in weka.gui.arffviewer
  This class fixes a bug with the Swing JFileChooser: if you entered a new filename in the save dialog and press Enter the `getSelectedFile` method returns `null` instead of the filename.
  To solve this annoying behavior we call the save dialog once again s.t.
FileChooser() - Constructor for class weka.gui.arffviewer.FileChooser
  default constructor, pointing to the user's default directory
FileChooser(String) - Constructor for class weka.gui.arffviewer.FileChooser
  sets the default directory to the given one
FileChooser(File) - Constructor for class weka.gui.arffviewer.FileChooser
  sets the default directory to the given one
FileEditor - Class in weka.gui
  A PropertyEditor for File objects that lets the user select a file.
FileEditor() - Constructor for class weka.gui.FileEditor
filePrefix() - Method in class weka.core.converters.AbstractFileSaver
  Gets the file name prefix
filePrefix() - Method in class weka.core.converters.AbstractSaver
  Default implementation throws an IOException.
filePrefix() - Method in interface weka.core.converters.Saver
  Gets the file prefix This method is used in the KnowledgeFlow GUI.
FileSourcedConverter - Interface in weka.core.converters
  Interface to a loader/saver that loads/saves from a file source.
fill(Shape) - Method in class weka.gui.visualize.PostscriptGraphics
fill3DRect(int, int, int, int, boolean) - Method in class weka.gui.visualize.PostscriptGraphics
  Draw a filled rectangle with 3D effect in current pen color.
fillArc(int, int, int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
  Not implemented
fillOval(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
  Draw a filled Oval in current pen color.
fillPolygon(int[], int[], int) - Method in class weka.gui.visualize.PostscriptGraphics
  Not implemented
fillPolygon(Polygon) - Method in class weka.gui.visualize.PostscriptGraphics
  Not implemented
fillRect(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
  Draw a filled rectangle in current pen color.
fillRoundRect(int, int, int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
  Not implemented
fillWithMissingTipText() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries
  Returns the tip text for this property
Filter - Class in weka.filters
  An abstract class for instance filters: objects that take instances as input, carry out some transformation on the instance and then output the instance.
Filter() - Constructor for class weka.filters.Filter
Filter - Class in weka.gui.beans
  A wrapper bean for Weka filters
Filter() - Constructor for class weka.gui.beans.Filter
FILTER_NONE - Static variable in class weka.classifiers.functions.SMO
FILTER_NONE - Static variable in class weka.classifiers.functions.SMOreg
FILTER_NORMALIZE - Static variable in class weka.classifiers.functions.SMO
  The filter to apply to the training data
FILTER_NORMALIZE - Static variable in class weka.classifiers.functions.SMOreg
  The filter to apply to the training data
FILTER_STANDARDIZE - Static variable in class weka.classifiers.functions.SMO
FILTER_STANDARDIZE - Static variable in class weka.classifiers.functions.SMOreg
FilterBeanInfo - Class in weka.gui.beans
  Bean info class for the Filter bean
FilterBeanInfo() - Constructor for class weka.gui.beans.FilterBeanInfo
FilterCustomizer - Class in weka.gui.beans
  GUI customizer for the filter bean
FilterCustomizer() - Constructor for class weka.gui.beans.FilterCustomizer
FilteredClassifier - Class in weka.classifiers.meta
  Class for running an arbitrary classifier on data that has been passed through an arbitrary filter.
FilteredClassifier() - Constructor for class weka.classifiers.meta.FilteredClassifier
  Default constructor.
filterFile(Filter, String[]) - Static method in class weka.filters.Filter
  Method for testing filters.
filterTipText() - Method in class weka.classifiers.meta.FilteredClassifier
  Returns the tip text for this property
filterTypeTipText() - Method in class weka.attributeSelection.SVMAttributeEval
  Returns a tip text for this property suitable for display in the GUI
filterTypeTipText() - Method in class weka.classifiers.functions.SMO
  Returns the tip text for this property
filterTypeTipText() - Method in class weka.classifiers.functions.SMOreg
  Returns the tip text for this property
finalize() - Method in class weka.gui.visualize.PostscriptGraphics
  Not implemented
find(String) - Static method in class weka.core.RTSI
  Returns all the classes inheriting or implementing a given class in the currently loaded packages.
  Note: If a package, containing subclasses, has not been loaded by the time of this method call, these classes won't be found! It's better to define the package name explicitly in which to look for subclasses, like in `find(String,String)`.
find(String, String) - Static method in class weka.core.RTSI
  Returns all the classes inheriting or implementing a given class in a given package.
find(String, Class) - Static method in class weka.core.RTSI
  Return all the classes inheriting or implementing a given class in a given package.
findArgmin(double[], double[][]) - Method in class weka.core.Optimization
  Main algorithm.
findBestLeaf(double[], RuleNode[]) - Method in class weka.classifiers.trees.m5.RuleNode
  Find the leaf with greatest coverage
findCentralTendencies(double[]) - Method in class weka.classifiers.BVDecomposeSegCVSub
  Finds the central tendency, given the classifications for an instance.
findInstance(Point) - Static method in class weka.gui.beans.BeanInstance
  Looks for a bean (if any) whose bounds contain the supplied point
findInstances(Rectangle) - Static method in class weka.gui.beans.BeanInstance
  Looks for all beans (if any) located within the supplied bounding box
findIntervall(double) - Method in class weka.associations.PriorEstimation
  searches the mid point of the interval a given confidence value falls into
findNumBinsTipText() - Method in class weka.filters.unsupervised.attribute.Discretize
  Returns the tip text for this property
findNumBinsTipText() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize
  Returns the tip text for this property
findReadMethod(Object, String) - Static method in class weka.core.xml.XMLSerializationMethodHandler
  returns the method with the given name that has the same signature as `readFromXML()` of the `XMLSerialiation` class.
findWriteMethod(Object, String) - Static method in class weka.core.xml.XMLSerializationMethodHandler
  returns the method with the given name that has the same signature as `writeToXML()` of the `XMLSerialiation` class.
finished() - Method in class weka.experiment.OutputZipper
  Closes the zip file.
FINISHED - Static variable in class weka.experiment.TaskStatusInfo
finished() - Method in class weka.gui.visualize.PostscriptGraphics
  Finalizes output file.
fireLayoutCompleteEvent(LayoutCompleteEvent) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine
  Fires a LayoutCompleteEvent.
fireLayoutCompleteEvent(LayoutCompleteEvent) - Method in interface weka.gui.graphvisualizer.LayoutEngine
  This fires a LayoutCompleteEvent once a layout has been completed.
firstElement() - Method in class weka.core.FastVector
  Returns the first element of the vector.
firstInstance() - Method in class weka.core.Instances
  Returns the first instance in the set.
FirstOrder - Class in weka.filters.unsupervised.attribute
  This instance filter takes a range of N numeric attributes and replaces them with N-1 numeric attributes, the values of which are the difference between consecutive attribute values from the original instance.
FirstOrder() - Constructor for class weka.filters.unsupervised.attribute.FirstOrder
firstValueIndexTipText() - Method in class weka.filters.unsupervised.attribute.SwapValues
firstValueTipText() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues
fit(DoubleVector) - Method in class weka.classifiers.functions.pace.MixtureDistribution
  Fits the mixture (or mixing) distribution to the data.
fit(DoubleVector, int) - Method in class weka.classifiers.functions.pace.MixtureDistribution
  Fits the mixture (or mixing) distribution to the data.
fitForSingleCluster(DoubleVector, int) - Method in class weka.classifiers.functions.pace.MixtureDistribution
  Fits the mixture (or mixing) distribution to the data.
fittingIntervals(DoubleVector) - Method in class weka.classifiers.functions.pace.ChisqMixture
  Contructs the set of fitting intervals for mixture estimation.
fittingIntervals(DoubleVector) - Method in class weka.classifiers.functions.pace.MixtureDistribution
  Contructs the set of fitting intervals for mixture estimation.
fittingIntervals(DoubleVector) - Method in class weka.classifiers.functions.pace.NormalMixture
  Contructs the set of fitting intervals for mixture estimation.
fitToScreen() - Method in class weka.gui.treevisualizer.TreeVisualizer
  Fits the tree to the current screen size.
FlexibleDecimalFormat - Class in weka.classifiers.functions.pace
FlexibleDecimalFormat() - Constructor for class weka.classifiers.functions.pace.FlexibleDecimalFormat
FlexibleDecimalFormat(int) - Constructor for class weka.classifiers.functions.pace.FlexibleDecimalFormat
FlexibleDecimalFormat(int, boolean) - Constructor for class weka.classifiers.functions.pace.FlexibleDecimalFormat
FlexibleDecimalFormat(int, boolean, boolean, boolean) - Constructor for class weka.classifiers.functions.pace.FlexibleDecimalFormat
FlexibleDecimalFormat(double) - Constructor for class weka.classifiers.functions.pace.FlexibleDecimalFormat
FLOAT - Static variable in class weka.core.converters.DatabaseLoader
FLOAT - Static variable in class weka.experiment.DatabaseUtils
  Type mapping for FLOAT used for reading experiment results
FloatingPointFormat - Class in weka.classifiers.functions.pace
  Class for the format of floating point numbers
FloatingPointFormat() - Constructor for class weka.classifiers.functions.pace.FloatingPointFormat
  Default constructor
FloatingPointFormat(int) - Constructor for class weka.classifiers.functions.pace.FloatingPointFormat
FloatingPointFormat(int, int) - Constructor for class weka.classifiers.functions.pace.FloatingPointFormat
FloatingPointFormat(int, int, boolean) - Constructor for class weka.classifiers.functions.pace.FloatingPointFormat
FLOOR - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
FLOOR1 - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
fMeasure(int) - Method in class weka.classifiers.Evaluation
  Calculate the F-Measure with respect to a particular class.
FMEASURE_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve
FOLD_FIELD_NAME - Static variable in class weka.experiment.CrossValidationResultProducer
foldsTipText() - Method in class weka.attributeSelection.OneRAttributeEval
  Returns a string for this option suitable for display in the gui as a tip text
foldsTipText() - Method in class weka.attributeSelection.RaceSearch
  Returns the tip text for this property
foldsTipText() - Method in class weka.attributeSelection.WrapperSubsetEval
  Returns the tip text for this property
foldsTipText() - Method in class weka.classifiers.rules.ConjunctiveRule
  Returns the tip text for this property
foldsTipText() - Method in class weka.classifiers.rules.JRip
  Returns the tip text for this property
foldsTipText() - Method in class weka.classifiers.rules.Ridor
  Returns the tip text for this property
foldsTipText() - Method in class weka.gui.beans.CrossValidationFoldMaker
  Tip text for this property
foldTipText() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds
  Returns the tip text for this property
foldTipText() - Method in class weka.filters.unsupervised.instance.RemoveFolds
  Returns the tip text for this property
format(double, StringBuffer, FieldPosition) - Method in class weka.classifiers.functions.pace.ExponentialFormat
format(double, StringBuffer, FieldPosition) - Method in class weka.classifiers.functions.pace.FlexibleDecimalFormat
format(double, StringBuffer, FieldPosition) - Method in class weka.classifiers.functions.pace.FloatingPointFormat
FORMAT_AVAILABLE - Static variable in class weka.gui.beans.InstanceEvent
FORMAT_AVAILABLE - Static variable in class weka.gui.streams.InstanceEvent
  Specifies that the instance format is available
formatDate(double) - Method in class weka.core.Attribute
formatString(String) - Method in class weka.classifiers.functions.pace.FlexibleDecimalFormat
forName(String, String[]) - Static method in class weka.associations.Associator
  Creates a new instance of a associator given it's class name and (optional) arguments to pass to it's setOptions method.
forName(String, String[]) - Static method in class weka.attributeSelection.ASEvaluation
  Creates a new instance of an attribute/subset evaluator given it's class name and (optional) arguments to pass to it's setOptions method.
forName(String, String[]) - Static method in class weka.attributeSelection.ASSearch
  Creates a new instance of a search class given it's class name and (optional) arguments to pass to it's setOptions method.
forName(String, String[]) - Static method in class weka.classifiers.Classifier
  Creates a new instance of a classifier given it's class name and (optional) arguments to pass to it's setOptions method.
forName(String, String[]) - Static method in class weka.clusterers.Clusterer
  Creates a new instance of a clusterer given it's class name and (optional) arguments to pass to it's setOptions method.
forName(Class, String, String[]) - Static method in class weka.core.Utils
  Creates a new instance of an object given it's class name and (optional) arguments to pass to it's setOptions method.
forward(PaceMatrix, IntVector, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Forward ordering of columns in terms of response explanation.
foundUsefulAttribute() - Method in class weka.classifiers.functions.SimpleLinearRegression
  Returns true if a usable attribute was found.
FP_RATE_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve
FProbability(double, int, int) - Static method in class weka.core.Statistics
  Computes probability of F-ratio.
FREQ_ASCEND - Static variable in class weka.filters.supervised.attribute.ClassOrder
  The class values are sorted in ascending order based on their frequencies
FREQ_DESCEND - Static variable in class weka.filters.supervised.attribute.ClassOrder
  The class values are sorted in descending order based on their frequencies
frequencyThresholdTipText() - Method in class weka.associations.Tertius
  Returns the tip text for this property.
FromFile - Class in weka.classifiers.bayes.net.search.fixed
  The FromFile reads the structure of a Bayes net from a file in BIFF format.
FromFile() - Constructor for class weka.classifiers.bayes.net.search.fixed.FromFile
fromXML(Document) - Method in class weka.core.xml.XMLSerialization
  returns the given DOM document as an instance of the specified class
fullValue() - Method in class weka.gui.HierarchyPropertyParser
  The full value of the current node, i.e.

## G

g1(double, double) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Constructs the Givens rotation
g2(double[], int, int, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
gainRatio() - Method in class weka.classifiers.trees.j48.BinC45Split
  Returns (C4.5-type) gain ratio for the generated split.
gainRatio() - Method in class weka.classifiers.trees.j48.C45Split
  Returns (C4.5-type) gain ratio for the generated split.
gainRatio(double[][]) - Static method in class weka.core.ContingencyTables
  Computes gain ratio for contingency table (split on rows).
GainRatioAttributeEval - Class in weka.attributeSelection
  Class for Evaluating attributes individually by measuring gain ratio with respect to the class.
GainRatioAttributeEval() - Constructor for class weka.attributeSelection.GainRatioAttributeEval
  Constructor
GainRatioSplitCrit - Class in weka.classifiers.trees.j48
  Class for computing the gain ratio for a given distribution.
GainRatioSplitCrit() - Constructor for class weka.classifiers.trees.j48.GainRatioSplitCrit
gammaTipText() - Method in class weka.classifiers.functions.SMO
  Returns the tip text for this property
gammaTipText() - Method in class weka.classifiers.functions.SMOreg
  Returns the tip text for this property
GAUSSIAN - Static variable in class weka.filters.unsupervised.attribute.RandomProjection
  The types of distributions that can be used for calculating the random matrix
generateDistribution() - Method in class weka.associations.PriorEstimation
  Calculates the prior distribution.
generateExample() - Method in class weka.datagenerators.BIRCHCluster
  Generate an example of the dataset.
generateExample() - Method in class weka.datagenerators.RDG1
  Generate an example of the dataset dataset.
generateExamples() - Method in class weka.datagenerators.BIRCHCluster
  Generate all examples of the dataset.
generateExamples(Random, Instances) - Method in class weka.datagenerators.BIRCHCluster
  Generate all examples of the dataset.
generateExamples() - Method in class weka.datagenerators.RDG1
  Generate all examples of the dataset.
generateExamples(int, Random, Instances) - Method in class weka.datagenerators.RDG1
  Generate all examples of the dataset.
generateFinished() - Method in class weka.datagenerators.BIRCHCluster
  Compiles documentation about the data generation after the generation process
generateFinished() - Method in class weka.datagenerators.RDG1
  Compiles documentation about the data generation.
generateInstances() - Method in class weka.classifiers.bayes.net.BayesNetGenerator
generateInstances(int[]) - Method in interface weka.gui.boundaryvisualizer.DataGenerator
  Generate an instance.
generateInstances(int[]) - Method in class weka.gui.boundaryvisualizer.KDDataGenerator
  Generates a new instance using one kernel estimator.
generateRandomNetwork() - Method in class weka.classifiers.bayes.net.BayesNetGenerator
generateRandomNetworkStructure(int, int) - Method in class weka.classifiers.bayes.net.BayesNetGenerator
generateRankingTipText() - Method in class weka.attributeSelection.GreedyStepwise
  Returns the tip text for this property
generateRankingTipText() - Method in class weka.attributeSelection.RaceSearch
  Returns the tip text for this property
generateRankingTipText() - Method in class weka.attributeSelection.Ranker
  Returns the tip text for this property
generateRuleItem(ItemSet, ItemSet, Instances, int, int, double[], Hashtable) - Method in class weka.associations.RuleItem
  Constructs a new RuleItem if the support of the given rule is above the support threshold.
generateRules(double, FastVector, int) - Method in class weka.associations.AprioriItemSet
  Generates all rules for an item set.
generateRules(double, boolean) - Method in class weka.associations.LabeledItemSet
  Generates rules out of item sets
generateRules(int, double[], Hashtable, double, Instances, TreeSet, int) - Method in class weka.associations.RuleGeneration
  Generates all rules for an item set.
generateRulesBruteForce(double, int, FastVector, int, int, double) - Method in class weka.associations.AprioriItemSet
  Generates all significant rules for an item set.
generateStart() - Method in class weka.datagenerators.BIRCHCluster
  Compiles documentation about the data generation before the generation process
Generator - Class in weka.datagenerators
  Abstract class for data generators.
Generator() - Constructor for class weka.datagenerators.Generator
GeneratorPropertyIteratorPanel - Class in weka.gui.experiment
  This panel controls setting a list of values for an arbitrary resultgenerator property for an experiment to iterate over.
GeneratorPropertyIteratorPanel() - Constructor for class weka.gui.experiment.GeneratorPropertyIteratorPanel
  Creates the property iterator panel initially disabled.
GeneratorPropertyIteratorPanel(Experiment) - Constructor for class weka.gui.experiment.GeneratorPropertyIteratorPanel
  Creates the property iterator panel and sets the experiment.
GenericArrayEditor - Class in weka.gui
  A PropertyEditor for arrays of objects that themselves have property editors.
GenericArrayEditor() - Constructor for class weka.gui.GenericArrayEditor
  Sets up the array editor.
GenericObjectEditor - Class in weka.gui
  A PropertyEditor for objects.
GenericObjectEditor() - Constructor for class weka.gui.GenericObjectEditor
  Default constructor.
GenericObjectEditor(boolean) - Constructor for class weka.gui.GenericObjectEditor
  Constructor that allows specifying whether it is possible to change the class within the editor dialog.
GenericObjectEditor.GOEPanel - Class in weka.gui
  Handles the GUI side of editing values.
GenericObjectEditor.GOEPanel() - Constructor for class weka.gui.GenericObjectEditor.GOEPanel
  Creates the GUI editor component
GenericObjectEditor.JTreePopupMenu - Class in weka.gui
  Creates a popup menu containing a tree that is aware of the screen dimensions.
GenericObjectEditor.JTreePopupMenu(JTree) - Constructor for class weka.gui.GenericObjectEditor.JTreePopupMenu
  Constructs a new popup menu.
GenericPropertiesCreator - Class in weka.gui
  This class can generate the properties object that is normally loaded from the `GenericObjectEditor.props` file (= PROPERTY_FILE).
GenericPropertiesCreator() - Constructor for class weka.gui.GenericPropertiesCreator
  initializes the creator, locates the props file with the Utils class.
GenericPropertiesCreator(String) - Constructor for class weka.gui.GenericPropertiesCreator
  initializes the creator, the given file overrides the props-file search of the Utils class
GeneticSearch - Class in weka.attributeSelection
  Class for performing a genetic based search.
GeneticSearch() - Constructor for class weka.attributeSelection.GeneticSearch
  Constructor.
GeneticSearch - Class in weka.classifiers.bayes.net.search.global
  GeneticSearch is a crude implementation of genetic search for learning Bayesian network structures.
GeneticSearch() - Constructor for class weka.classifiers.bayes.net.search.global.GeneticSearch
GeneticSearch - Class in weka.classifiers.bayes.net.search.local
  GeneticSearch is a crude implementation of genetic search for learning Bayesian network structures.
GeneticSearch() - Constructor for class weka.classifiers.bayes.net.search.local.GeneticSearch
get(int) - Method in class weka.classifiers.functions.pace.DoubleVector
  Gets a single element.
get(int) - Method in class weka.classifiers.functions.pace.IntVector
  Gets the value of an element.
get(int, int) - Method in class weka.classifiers.functions.pace.Matrix
  Get a single element.
get(int, int) - Method in class weka.core.matrix.Matrix
  Get a single element.
get(String) - Method in class weka.core.xml.MethodHandler
  returns the stored method for the given property
get(Class) - Method in class weka.core.xml.MethodHandler
  returns the stored method for the given class
get(String, String) - Static method in class weka.gui.experiment.ExperimenterDefaults
  returns the value for the specified property, if non-existent then the default value.
getAboutPanel() - Method in class weka.gui.PropertySheetPanel
  Return the panel containing global info and help for the object being edited.
getAcuity() - Method in class weka.clusterers.Cobweb
  get the acuity value
getAdjustWeights() - Method in class weka.filters.supervised.instance.SpreadSubsample
  Returns true if instance weights will be adjusted to maintain total weight per class.
getADTree() - Method in class weka.classifiers.bayes.BayesNet
  get ADTree strucrture containing efficient representation of counts.
getAdvanceDataSetFirst() - Method in class weka.experiment.Experiment
  Get the value of m_DataSetFirstFirst.
getAlpha() - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator
  Get prior used in probability table estimation
getAlpha() - Method in class weka.classifiers.functions.Winnow
  Get the value of Alpha.
getAnimatedIcon() - Method in class weka.gui.beans.BeanVisual
  Returns the animated icon
getAnimatedIconPath() - Method in class weka.gui.beans.BeanVisual
  returns the path for the animated icon
getAppendPredictedProbabilities() - Method in class weka.gui.beans.PredictionAppender
  Return true if predicted probabilities are to be appended rather than class value
getArffFile() - Method in class weka.gui.streams.InstanceLoader
getArffFile() - Method in class weka.gui.streams.InstanceSavePanel
getArray() - Method in class weka.classifiers.functions.pace.Matrix
  Access the internal two-dimensional array.
getArray() - Method in class weka.core.matrix.Matrix
  Access the internal two-dimensional array.
getArrayClass(Class) - Static method in class weka.core.Utils
  Returns the basic class of an array class (handles multi-dimensional arrays).
getArrayCopy() - Method in class weka.classifiers.functions.pace.DoubleVector
  Returns a copy of the DoubleVector usng a double array.
getArrayCopy() - Method in class weka.classifiers.functions.pace.IntVector
  Returns a copy of the internal one-dimensional array.
getArrayCopy() - Method in class weka.classifiers.functions.pace.Matrix
  Copy the internal two-dimensional array.
getArrayCopy() - Method in class weka.core.matrix.Matrix
  Copy the internal two-dimensional array.
getArrayDimensions(Class) - Static method in class weka.core.Utils
  Returns the dimensions of the given array.
getArrayDimensions(Object) - Static method in class weka.core.Utils
  Returns the dimensions of the given array.
getArtificialSize() - Method in class weka.classifiers.meta.Decorate
  Factor that determines number of artificial examples to generate.
getAssociatedConnections() - Method in class weka.gui.beans.MetaBean
getAsText() - Method in class weka.gui.CostMatrixEditor
  Some objects can be represented as text, but a cost matrix cannot.
getAsText() - Method in class weka.gui.GenericArrayEditor
  Returns null as we don't support getting/setting values as text.
getAsText() - Method in class weka.gui.GenericObjectEditor
  Returns null as we don't support getting/setting values as text.
getAsText() - Method in class weka.gui.SelectedTagEditor
  Gets the current value as text.
getAsText() - Method in class weka.gui.SimpleDateFormatEditor
  Returns the date format string.
getAttIndex(int) - Method in class weka.classifiers.lazy.LBR.Indexes
  Returns the boolean value at the specified index in the Attribute Indexes array
getAttList_Irr() - Method in class weka.datagenerators.RDG1
  Gets the array that defines which of the attributes are seen to be irrelevant.
getAttribute1() - Method in class weka.gui.visualize.VisualizePanelEvent
getAttribute2() - Method in class weka.gui.visualize.VisualizePanelEvent
getAttributeAt(int) - Method in class weka.gui.arffviewer.ArffTableModel
  returns the attribute at the given index, can be NULL if not an attribute column
getAttributeAt(int) - Method in class weka.gui.arffviewer.ArffTableSorter
  returns the attribute at the given index, can be NULL if not an attribute column
getAttributeColumn(String) - Method in class weka.gui.arffviewer.ArffTableModel
  returns the column of the given attribute name, -1 if not found
getAttributeColumn(String) - Method in class weka.gui.arffviewer.ArffTableSorter
  returns the column of the given attribute name, -1 if not found
getAttributeEvaluator() - Method in class weka.attributeSelection.RaceSearch
  Get the attribute evaluator used to generate the ranking.
getAttributeEvaluator() - Method in class weka.attributeSelection.RankSearch
  Get the attribute evaluator used to generate the ranking.
getAttributeID() - Method in class weka.experiment.ClassifierSplitEvaluator
  Get the index of Attibute Identifying the instances
getAttributeIndex() - Method in class weka.classifiers.functions.SimpleLinearRegression
  Returns the index of the attribute used in the regression.
getAttributeIndex() - Method in class weka.filters.unsupervised.attribute.Add
  Get the index of the attribute used.
getAttributeIndex() - Method in class weka.filters.unsupervised.attribute.AddNoise
  Get the index of the attribute used.
getAttributeIndex() - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat
  Gets the index of the attribute converted.
getAttributeIndex() - Method in class weka.filters.unsupervised.attribute.MakeIndicator
  Get the index of the attribute used.
getAttributeIndex() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues
  Get the index of the attribute used.
getAttributeIndex() - Method in class weka.filters.unsupervised.attribute.StringToNominal
  Get the index of the attribute used.
getAttributeIndex() - Method in class weka.filters.unsupervised.attribute.SwapValues
  Get the index of the attribute used.
getAttributeIndex() - Method in class weka.filters.unsupervised.instance.RemoveWithValues
  Get the index of the attribute used.
getAttributeIndices() - Method in class weka.filters.supervised.attribute.Discretize
  Gets the current range selection
getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries
  Get the current range selection
getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.Copy
  Get the current range selection
getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.Discretize
  Gets the current range selection
getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.FirstOrder
  Get the current range selection
getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.NominalToBinary
  Gets the current range selection
getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.NumericTransform
  Get the current range selection
getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.Remove
  Get the current range selection.
getAttributeMax(int) - Method in class weka.classifiers.lazy.IBk
  Get an attributes maximum observed value
getAttributeMin(int) - Method in class weka.classifiers.lazy.IBk
  Get an attributes minimum observed value
getAttributeName() - Method in class weka.filters.unsupervised.attribute.Add
  Get the name of the attribute to be created
getAttributeNamePrefix() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Get the attribute name prefix.
getAttributes() - Method in class weka.gui.arffviewer.ArffPanel
  returns a list with the attributes
getAttributeSelectionMethod() - Method in class weka.classifiers.functions.LinearRegression
  Gets the method used to select attributes for use in the linear regression.
getAttributeType() - Method in class weka.filters.unsupervised.attribute.RemoveType
  Gets the attribute type to be deleted by the filter.
getAttsToEliminatePerIteration() - Method in class weka.attributeSelection.SVMAttributeEval
  Get the constant rate of attribute elimination per iteration
getAutoBuild() - Method in class weka.classifiers.functions.MultilayerPerceptron
getAutoKeyGeneration() - Method in class weka.core.converters.DatabaseSaver
  Gets whether or not a primary key will be generated automatically
getBackground() - Method in class weka.gui.visualize.JPEGWriter
  returns the current background color
getBackground() - Method in class weka.gui.visualize.PostscriptGraphics
getBackup() - Method in class weka.gui.GenericObjectEditor
  Returns the backup object (may be null if there is no backup).
getBagSizePercent() - Method in class weka.classifiers.meta.Bagging
  Gets the size of each bag, as a percentage of the training set size.
getBagSizePercent() - Method in class weka.classifiers.meta.MetaCost
  Gets the size of each bag, as a percentage of the training set size.
getBalanced() - Method in class weka.classifiers.functions.Winnow
  Get the value of Balanced.
getBaseExperiment() - Method in class weka.experiment.RemoteExperiment
  Get the base experiment used by this remote experiment
getBean() - Method in class weka.gui.beans.BeanInstance
  Gets the bean encapsulated in this instance
getBeanContext() - Method in class weka.gui.beans.AbstractDataSource
  Return the bean context (if any) that this bean is embedded in
getBeanContext() - Method in class weka.gui.beans.DataVisualizer
  Return the bean context (if any) that this bean is embedded in
getBeanContext() - Method in class weka.gui.beans.ModelPerformanceChart
  Return the bean context (if any) that this bean is embedded in
getBeanContext() - Method in class weka.gui.beans.TextViewer
  Return the bean context (if any) that this bean is embedded in
getBeanDescriptor() - Method in class weka.gui.beans.ClassAssignerBeanInfo
getBeanDescriptor() - Method in class weka.gui.beans.ClassifierBeanInfo
  Get the bean descriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.ClassValuePickerBeanInfo
getBeanDescriptor() - Method in class weka.gui.beans.ClustererBeanInfo
  Get the bean descriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.CrossValidationFoldMakerBeanInfo
  Return the bean descriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.FilterBeanInfo
  Get the bean descriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.LoaderBeanInfo
  Get the bean descriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.PredictionAppenderBeanInfo
  Return the bean descriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.SaverBeanInfo
  Get the bean descriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.StripChartBeanInfo
  Get the bean descriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.TrainTestSplitMakerBeanInfo
  Get the bean descriptor for this bean
getBeanInfoInputs() - Method in class weka.gui.beans.MetaBean
getBeanInfoOutputs() - Method in class weka.gui.beans.MetaBean
getBeanInfoSubFlow() - Method in class weka.gui.beans.MetaBean
getBeanInstances() - Static method in class weka.gui.beans.BeanInstance
  Return the list of displayed beans
getBeansInInputs() - Method in class weka.gui.beans.MetaBean
  Return all the beans in the inputs
getBeansInOutputs() - Method in class weka.gui.beans.MetaBean
  Return all the beans in the outputs
getBeansInSubFlow() - Method in class weka.gui.beans.MetaBean
  Return all the beans in the sub flow
getBestCommitteeChunkSize() - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost
  Get the best committee chunk size
getBestCommitteeErrorEstimate() - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost
  Get the best committee's error on the validation data
getBestCommitteeLLEstimate() - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost
  Get the best committee's log likelihood on the validation data
getBestCommitteeSize() - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost
  Get the number of members in the best committee
getBeta() - Method in class weka.classifiers.functions.Winnow
  Get the value of Beta.
getBias() - Method in class weka.classifiers.BVDecompose
  Get the calculated bias squared
getBias() - Method in class weka.classifiers.misc.VFI
  Get the value of the bias parameter
getBiasToUniformClass() - Method in class weka.filters.supervised.instance.Resample
  Gets the bias towards a uniform class.
getBIFFile() - Method in class weka.classifiers.bayes.BayesNet
  Get name of network in BIF file to compare with
getBIFFile() - Method in class weka.classifiers.bayes.net.search.fixed.FromFile
  Get name of network in BIF file to read structure from
getBinarizeNumericAttributes() - Method in class weka.attributeSelection.ChiSquaredAttributeEval
  get whether numeric attributes are just being binarized.
getBinarizeNumericAttributes() - Method in class weka.attributeSelection.InfoGainAttributeEval
  get whether numeric attributes are just being binarized.
getBinaryAttributesNominal() - Method in class weka.filters.supervised.attribute.NominalToBinary
  Gets if binary attributes are to be treated as nominal ones.
getBinaryAttributesNominal() - Method in class weka.filters.unsupervised.attribute.NominalToBinary
  Gets if binary attributes are to be treated as nominal ones.
getBinarySplits() - Method in class weka.classifiers.rules.PART
  Get the value of binarySplits.
getBinarySplits() - Method in class weka.classifiers.trees.J48
  Get the value of binarySplits.
getBins() - Method in class weka.filters.unsupervised.attribute.Discretize
  Gets the number of bins numeric attributes will be divided into
getBins() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize
  Ignored
getBuilder() - Method in class weka.core.xml.XMLDocument
  returns the DocumentBuilder
getBuildLogisticModels() - Method in class weka.classifiers.functions.SMO
  Get the value of buildLogisticModels.
getBuildRegressionTree() - Method in class weka.classifiers.trees.m5.M5Base
  Get the value of regressionTree.
getC() - Method in class weka.classifiers.functions.SMO
  Get the value of C.
getC() - Method in class weka.classifiers.functions.SMOreg
  Get the value of C.
getCacheKeyName() - Method in class weka.experiment.DatabaseResultListener
  Get the value of CacheKeyName.
getCacheSize() - Method in class weka.classifiers.functions.SMO
  Get the size of the kernel cache
getCacheSize() - Method in class weka.classifiers.functions.SMOreg
  Get the size of the kernel cache
getCacheValues(double) - Method in class weka.classifiers.lazy.kstar.KStarCache
  Returns the values in the cache mapped by the specified key
getCalcOutOfBag() - Method in class weka.classifiers.meta.Bagging
  Get whether the out of bag error is calculated.
getCalculatedNumToSelect() - Method in class weka.attributeSelection.GreedyStepwise
  Gets the calculated number of attributes to retain.
getCalculatedNumToSelect() - Method in class weka.attributeSelection.RaceSearch
  Gets the calculated number of attributes to retain.
getCalculatedNumToSelect() - Method in interface weka.attributeSelection.RankedOutputSearch
  Gets the calculated number of attributes to retain.
getCalculatedNumToSelect() - Method in class weka.attributeSelection.Ranker
  Gets the calculated number to select.
getCalculateStdDevs() - Method in class weka.experiment.AveragingResultProducer
  Get the value of CalculateStdDevs.
getCardinality(int) - Method in class weka.classifiers.bayes.BayesNet
  get number of values a node can take
getCardinalityOfParents() - Method in class weka.classifiers.bayes.net.ParentSet
  returns cardinality of parents
getCenter() - Method in class weka.gui.treevisualizer.Node
  Get the value of center.
getChangeInWeights() - Method in class weka.classifiers.functions.neural.NeuralNode
  call this function to get the chnage in weights array.
getCheckErrorRate() - Method in class weka.classifiers.rules.JRip
getChild(int) - Method in class weka.gui.treevisualizer.Node
  Get the Edge for the child number 'i'.
getChildForBranch(int) - Method in class weka.classifiers.trees.adtree.Splitter
  Gets the child for a branch of the split.
getChildForBranch(int) - Method in class weka.classifiers.trees.adtree.TwoWayNominalSplit
  Gets the child for a branch of the split.
getChildForBranch(int) - Method in class weka.classifiers.trees.adtree.TwoWayNumericSplit
  Gets the child for a branch of the split.
getChildren() - Method in class weka.classifiers.trees.adtree.PredictionNode
  Gets the children of this node.
getChildTags(Node) - Static method in class weka.core.xml.XMLDocument
  returns all non tag-children from the given node
getChooseClassPopupMenu() - Method in class weka.gui.GenericObjectEditor
  Returns a popup menu that allows the user to change the class of object.
getCindex() - Method in class weka.gui.visualize.PlotData2D
  Get the currently set colouring index of the data
getCIndex() - Method in class weka.gui.visualize.VisualizePanel
  Get the index of the attribute selected for coloring
getClassColumn() - Method in class weka.gui.beans.ClassAssigner
getClassCounts() - Method in class weka.filters.supervised.attribute.ClassOrder
  Get the class distribution of the sorted class values.
getClassesToClusters() - Method in class weka.clusterers.ClusterEvaluation
  Return the array (ordered by cluster number) of minimum error class to cluster mappings
getClassFlag() - Method in class weka.datagenerators.ClusterGenerator
  Gets the class flag.
getClassForIRStatistics() - Method in class weka.experiment.ClassifierSplitEvaluator
  Get the value of ClassForIRStatistics.
getClassification() - Method in class weka.associations.Tertius
  Get the value of classification.
getClassifier() - Method in class weka.attributeSelection.ClassifierSubsetEval
  Get the classifier used as the base learner.
getClassifier() - Method in class weka.attributeSelection.WrapperSubsetEval
  Get the classifier used as the base learner.
getClassifier() - Method in class weka.classifiers.BVDecompose
  Gets the name of the classifier being analysed
getClassifier() - Method in class weka.classifiers.BVDecomposeSegCVSub
  Gets the name of the classifier being analysed
getClassifier() - Method in class weka.classifiers.CheckClassifier
  Get the classifier used as the classifier
getClassifier(int) - Method in class weka.classifiers.meta.MultiScheme
  Gets a single classifier from the set of available classifiers.
getClassifier(int) - Method in class weka.classifiers.MultipleClassifiersCombiner
  Gets a single classifier from the set of available classifiers.
getClassifier() - Method in class weka.classifiers.SingleClassifierEnhancer
  Get the classifier used as the base learner.
getClassifier() - Method in class weka.experiment.ClassifierSplitEvaluator
  Get the value of Classifier.
getClassifier() - Method in class weka.experiment.RegressionSplitEvaluator
  Get the value of Classifier.
getClassifier() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified
  Gets the classifier used by the filter.
getClassifier() - Method in class weka.gui.beans.BatchClassifierEvent
  Get the classifier
getClassifier() - Method in class weka.gui.beans.Classifier
  Get the classifier currently set for this wrapper
getClassifier() - Method in class weka.gui.beans.IncrementalClassifierEvent
  Get the classifier
getClassifiers() - Method in class weka.classifiers.meta.MultiScheme
  Gets the list of possible classifers to choose from.
getClassifiers() - Method in class weka.classifiers.MultipleClassifiersCombiner
  Gets the list of possible classifers to choose from.
getClassifyIterations() - Method in class weka.classifiers.BVDecomposeSegCVSub
  Gets the number of times an instance is classified
getClassIndex() - Method in class weka.associations.Tertius
  Get the value of classIndex.
getClassIndex() - Method in class weka.classifiers.BVDecompose
  Get the index (starting from 1) of the attribute used as the class.
getClassIndex() - Method in class weka.classifiers.BVDecomposeSegCVSub
  Get the index (starting from 1) of the attribute used as the class.
getClassIndex() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified
  Gets the attribute on which misclassifications are based.
getClassName() - Method in class weka.filters.unsupervised.attribute.NumericTransform
  Get the class containing the transformation method.
getClassOrder() - Method in class weka.filters.supervised.attribute.ClassOrder
  Get the wanted class order
getClassValueIndex() - Method in class weka.gui.beans.ClassValuePicker
  Gets the class value index considered to be the "positive" class value.
getClearEachDataset() - Method in class weka.gui.streams.InstanceViewer
getClip() - Method in class weka.gui.visualize.PostscriptGraphics
  Not implemented
getClipBounds() - Method in class weka.gui.visualize.PostscriptGraphics
  This returns the full current drawing area
getClipBounds(Rectangle) - Method in class weka.gui.visualize.PostscriptGraphics
  This returns the full current drawing area
getClipRect() - Method in class weka.gui.visualize.PostscriptGraphics
  Not implemented
getClosestConnections(Point, int) - Static method in class weka.gui.beans.BeanConnection
  Return a list of connections within some delta of a point
getClosestConnectorPoint(Point) - Method in class weka.gui.beans.BeanVisual
  Returns the coordinates of the closest "connector" point to the supplied point.
getClusterAssignments() - Method in class weka.clusterers.ClusterEvaluation
  Return an array of cluster assignments corresponding to the most recent set of instances clustered.
getClusterCentroids() - Method in class weka.clusterers.SimpleKMeans
getClusterer() - Method in class weka.clusterers.MakeDensityBasedClusterer
  Gets the clusterer being wrapped.
getClusterer() - Method in class weka.filters.unsupervised.attribute.AddCluster
  Gets the clusterer used by the filter.
getClusterer() - Method in class weka.gui.beans.BatchClustererEvent
  Get the clusterer
getClusterer() - Method in class weka.gui.beans.Clusterer
  Get the clusterer currently set for this wrapper
getClusteringSeed() - Method in class weka.classifiers.functions.RBFNetwork
  Get the random seed used by K-means.
getClusterModelsNumericAtts() - Method in class weka.clusterers.EM
  Return the normal distributions for the cluster models
getClusterNominalCounts() - Method in class weka.clusterers.SimpleKMeans
getClusterPriors() - Method in class weka.clusterers.EM
  Return the priors for the clusters
getClusterSizes() - Method in class weka.clusterers.SimpleKMeans
getClusterStandardDevs() - Method in class weka.clusterers.SimpleKMeans
getCoefficients() - Method in class weka.core.matrix.LinearRegression
  returns the calculated coefficients
getColor() - Method in class weka.gui.treevisualizer.Node
  Get the value of color.
getColor() - Method in class weka.gui.visualize.PostscriptGraphics
  Get current pen color.
getColorBox() - Method in class weka.gui.AttributeVisualizationPanel
  Returns the class selection combo box if the parent component wants to place it in itself or in some component other than this component.
getColoringIndex() - Method in class weka.gui.AttributeVisualizationPanel
  Get the coloring (class) index for the plot
getColoringIndex() - Method in class weka.gui.beans.AttributeSummarizer
  Return the coloring index for the attribute summary plots
getColors() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel
  Get the current vector of Color objects used for the classes
getColumn(int) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Return a DoubleVector that stores a column of the matrix
getColumn(int, int, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Return a DoubleVector that stores some elements of a column of the matrix
getColumn(int) - Method in class weka.core.Matrix
  Deprecated. Gets a column of the matrix and returns it as a double array.
getColumn() - Static method in class weka.gui.experiment.ExperimenterDefaults
  the comma-separated list of attribute names that identify a column
getColumnClass(int) - Method in class weka.gui.arffviewer.ArffTableModel
  returns the most specific superclass for all the cell values in the column (always String)
getColumnClass(int) - Method in class weka.gui.TableMap
getColumnCount() - Method in class weka.gui.arffviewer.ArffTableModel
  returns the number of columns in the model
getColumnCount() - Method in class weka.gui.TableMap
getColumnDimension() - Method in class weka.classifiers.functions.pace.Matrix
  Get column dimension.
getColumnDimension() - Method in class weka.core.matrix.Matrix
  Get column dimension.
getColumnName(int) - Method in class weka.gui.arffviewer.ArffTableModel
  returns the name of the column at columnIndex
getColumnName(int) - Method in class weka.gui.TableMap
getColumnPackedCopy() - Method in class weka.classifiers.functions.pace.Matrix
  Make a one-dimensional column packed copy of the internal array.
getColumnPackedCopy() - Method in class weka.core.matrix.Matrix
  Make a one-dimensional column packed copy of the internal array.
getCommand() - Method in class weka.gui.treevisualizer.TreeDisplayEvent
getComparisonField() - Static method in class weka.gui.experiment.ExperimenterDefaults
  returns the name of the field used for comparison
getCompatibilityState() - Method in class weka.experiment.AveragingResultProducer
  Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface).
getCompatibilityState() - Method in class weka.experiment.CrossValidationResultProducer
  Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface).
getCompatibilityState() - Method in class weka.experiment.DatabaseResultProducer
  Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface).
getCompatibilityState() - Method in class weka.experiment.LearningRateResultProducer
  Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface).
getCompatibilityState() - Method in class weka.experiment.RandomSplitResultProducer
  Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface).
getCompatibilityState() - Method in interface weka.experiment.ResultProducer
  Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface).
getComplexityParameter() - Method in class weka.attributeSelection.SVMAttributeEval
  Get the value of C used with SMO
getComponent() - Method in class weka.gui.visualize.JComponentWriter
  returns the component that is stored in the output format
getComponent() - Method in class weka.gui.visualize.PrintableComponent
  returns the GUI component this print dialog is part of
getComposite() - Method in class weka.gui.visualize.PostscriptGraphics
getConfidenceFactor() - Method in class weka.classifiers.rules.PART
  Get the value of CF.
getConfidenceFactor() - Method in class weka.classifiers.trees.J48
  Get the value of CF.
getConfirmation() - Method in class weka.associations.tertius.Rule
  Get the confirmation value of this rule.
getConfirmationThreshold() - Method in class weka.associations.Tertius
  Get the value of confirmationThreshold.
getConfirmationValues() - Method in class weka.associations.Tertius
  Get the value of confirmationValues.
getConfirmExit() - Method in class weka.gui.arffviewer.ArffViewer
  returns the setting of whether to display a confirm messagebox or not on exit
getConfirmExit() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  returns the setting of whether to display a confirm messagebox or not on exit
getConfusionMatrix() - Method in class weka.classifiers.evaluation.TwoClassStats
  Generates a `ConfusionMatrix` representing the current two-class statistics, using class names "negative" and "positive".
getConnectedFormat() - Method in class weka.gui.beans.ClassAssigner
  Returns the structure of the incoming instances (if any)
getConnectedFormat() - Method in class weka.gui.beans.ClassValuePicker
  Returns the structure of the incoming instances (if any)
getConnections() - Static method in class weka.gui.beans.BeanConnection
  Returns the list of connections
getConnectorPoint(int) - Method in class weka.gui.beans.BeanVisual
  Returns the coordinates of the connector point given a compass point
getConsequent() - Method in class weka.classifiers.rules.Rule
  Get the consequent of this rule, i.e.
getContent(Element) - Method in class weka.classifiers.bayes.net.BIFReader
  Returns all TEXT children of the given node in one string.
getContent(Element) - Static method in class weka.core.xml.XMLDocument
  returns the text between the opening and closing tag of a node (performs a `trim()` on the result)
getControlPanel() - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine
  This method returns a handle to the extra controls panel, so that the visualizing class can add it to some of it's own gui panel.
getControlPanel() - Method in interface weka.gui.graphvisualizer.LayoutEngine
  This method returns the extra controls panel for the LayoutEngine, if there is any.
getConvertNominal() - Method in class weka.classifiers.trees.LMT
  Get the value of convertNominal.
getCostMatrix() - Method in class weka.classifiers.meta.CostSensitiveClassifier
  Gets the misclassification cost matrix.
getCostMatrix() - Method in class weka.classifiers.meta.MetaCost
  Gets the misclassification cost matrix.
getCostMatrixSource() - Method in class weka.classifiers.meta.CostSensitiveClassifier
  Gets the source location method of the cost matrix.
getCostMatrixSource() - Method in class weka.classifiers.meta.MetaCost
  Gets the source location method of the cost matrix.
getCount(double) - Method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes
  Get a counts for a value
getCount(double) - Method in class weka.estimators.DiscreteEstimator
  Get the count for a value
getCount(Node, int) - Static method in class weka.gui.treevisualizer.Node
  Recursively finds the number of visible nodes there are (this may accidentally count some of the invis nodes).
getCounterInstancesFrequency() - Method in class weka.associations.tertius.LiteralSet
  Get the frequency of counter-instances of this LiteralSet in the data.
getCounterInstancesNumber() - Method in class weka.associations.tertius.LiteralSet
  Get the number of counter-instances of this LiteralSet.
getCounts(int[], int[], int[], int, int, boolean) - Method in class weka.classifiers.bayes.net.ADNode
  get counts for specific instantiation of a set of nodes
getCounts(int[], int[], int[], int, int, ADNode, boolean) - Method in class weka.classifiers.bayes.net.VaryNode
  get counts for specific instantiation of a set of nodes
getCrossoverProb() - Method in class weka.attributeSelection.GeneticSearch
  get the probability of crossover
getCrossVal() - Method in class weka.classifiers.rules.DecisionTable
  Gets the number of folds for cross validation
getCrossValidate() - Method in class weka.classifiers.lazy.IBk
  Gets whether hold-one-out cross-validation will be used to select the best k value
getCurrent() - Method in class weka.core.Memory
  returns the current memory consumption
getCurrentDatasetNumber() - Method in class weka.experiment.Experiment
  When an experiment is running, this returns the current dataset number.
getCurrentFilename() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  returns the filename of the current tab
getCurrentIndex() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  returns the currently selected tab index
getCurrentInstance() - Method in class weka.gui.beans.IncrementalClassifierEvent
  Get the current instance
getCurrentPanel() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  returns the currently selected panel
getCurrentPropertyNumber() - Method in class weka.experiment.Experiment
  When an experiment is running, this returns the index of the current custom property value.
getCurrentRunNumber() - Method in class weka.experiment.Experiment
  When an experiment is running, this returns the current run number.
getCurve(FastVector) - Method in class weka.classifiers.evaluation.CostCurve
  Calculates the performance stats for the default class and return results as a set of Instances.
getCurve(FastVector, int) - Method in class weka.classifiers.evaluation.CostCurve
  Calculates the performance stats for the desired class and return results as a set of Instances.
getCurve(FastVector) - Method in class weka.classifiers.evaluation.MarginCurve
  Calculates the cumulative margin distribution for the set of predictions, returning the result as a set of Instances.
getCurve(FastVector) - Method in class weka.classifiers.evaluation.ThresholdCurve
  Calculates the performance stats for the default class and return results as a set of Instances.
getCurve(FastVector, int) - Method in class weka.classifiers.evaluation.ThresholdCurve
  Calculates the performance stats for the desired class and return results as a set of Instances.
getCustomEditor() - Method in class weka.gui.CostMatrixEditor
  Gets a GUI component with which the user can edit the cost matrix.
getCustomEditor() - Method in class weka.gui.FileEditor
  Gets the custom editor component.
getCustomEditor() - Method in class weka.gui.GenericArrayEditor
  Returns the array editing component.
getCustomEditor() - Method in class weka.gui.GenericObjectEditor
  Returns the array editing component.
getCustomEditor() - Method in class weka.gui.SimpleDateFormatEditor
  Gets a GUI component with which the user can edit the date format.
getCustomPanel() - Method in interface weka.gui.CustomPanelSupplier
  Gets the custom panel for the object.
getCustomPanel() - Method in class weka.gui.GenericObjectEditor
  Gets the custom panel used for editing the object.
getCutoff() - Method in class weka.clusterers.Cobweb
  get the cutoff
getCutPoints(int) - Method in class weka.filters.supervised.attribute.Discretize
  Gets the cut points for an attribute
getCutPoints(int) - Method in class weka.filters.unsupervised.attribute.Discretize
  Gets the cut points for an attribute
getCVisible() - Method in class weka.gui.treevisualizer.Node
  Get If this node's childs are visible.
getCVParameter(int) - Method in class weka.classifiers.meta.CVParameterSelection
  Gets the scheme paramter with the given index.
getCVParameters() - Method in class weka.classifiers.meta.CVParameterSelection
  Get method for CVParameters.
getCVPredictions(Classifier, Instances, int) - Method in class weka.classifiers.evaluation.EvaluationUtils
  Generate a bunch of predictions ready for processing, by performing a cross-validation on the supplied dataset.
getCVType() - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
  get cross validation strategy to be used in searching for networks.
getD() - Method in class weka.core.matrix.EigenvalueDecomposition
  Return the block diagonal eigenvalue matrix
getData() - Method in class weka.attributeSelection.BestFirst.Link2
  Get a group
getData() - Method in class weka.classifiers.rules.RuleStats
  Get the data of the stats
getDatabaseURL() - Method in class weka.experiment.DatabaseUtils
  Get the value of DatabaseURL.
getDataFileName() - Method in class weka.classifiers.BVDecompose
  Get the name of the data file used for the decomposition
getDataFileName() - Method in class weka.classifiers.BVDecomposeSegCVSub
  Get the name of the data file used for the decomposition
getDataPoint() - Method in class weka.gui.beans.ChartEvent
  Get the data point
getDataSet() - Method in class weka.core.converters.AbstractLoader
getDataSet() - Method in class weka.core.converters.ArffLoader
  Return the full data set.
getDataSet() - Method in class weka.core.converters.C45Loader
  Return the full data set.
getDataSet() - Method in class weka.core.converters.CSVLoader
  Return the full data set.
getDataSet() - Method in class weka.core.converters.DatabaseLoader
  Return the full data set in batch mode (header and all intances at once).
getDataSet() - Method in interface weka.core.converters.Loader
  Return the full data set.
getDataSet() - Method in class weka.core.converters.SerializedInstancesLoader
  Return the full data set.
getDataSet() - Method in class weka.gui.beans.DataSetEvent
  Return the instances of the data set
getDataSet() - Method in class weka.gui.beans.ThresholdDataEvent
  Return the instances of the data set
getDataSet() - Method in class weka.gui.beans.VisualizableErrorEvent
  Return the instances of the data set
getDatasetFormat() - Method in class weka.datagenerators.BIRCHCluster
  Gets the dataset format.
getDatasetFormat() - Method in class weka.datagenerators.RDG1
  Gets the dataset format.
getDatasetKeyColumns() - Method in class weka.experiment.PairedTTester
  Get the value of DatasetKeyColumns.
getDatasets() - Method in class weka.experiment.Experiment
  Gets the datasets in the experiment.
getDatasetsFirst() - Static method in class weka.gui.experiment.ExperimenterDefaults
  whether datasets or algorithms are iterated first
getDataType() - Method in class weka.gui.beans.xml.XMLBeans
  returns the type of data that is to be read/written
getDateFormat() - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat
  Get the date format used in output.
getDebug() - Method in class weka.attributeSelection.RaceSearch
  Get whether output is to be verbose
getDebug() - Method in class weka.classifiers.BVDecompose
  Gets whether debugging is turned on
getDebug() - Method in class weka.classifiers.BVDecomposeSegCVSub
  Gets whether debugging is turned on
getDebug() - Method in class weka.classifiers.CheckClassifier
  Get whether debugging is turned on
getDebug() - Method in class weka.classifiers.Classifier
  Get whether debugging is turned on.
getDebug() - Method in class weka.classifiers.functions.LeastMedSq
  Returns whether or not debugging output shouild be printed
getDebug() - Method in class weka.classifiers.functions.LinearRegression
  Controls whether debugging output will be printed
getDebug() - Method in class weka.classifiers.functions.Logistic
  Gets whether debugging output will be printed.
getDebug() - Method in class weka.classifiers.functions.PaceRegression
  Controls whether debugging output will be printed
getDebug() - Method in class weka.classifiers.meta.MultiScheme
  Get whether debugging is turned on
getDebug() - Method in class weka.classifiers.rules.JRip
getDebug() - Method in class weka.classifiers.trees.RandomTree
  Get the value of Debug.
getDebug() - Method in class weka.clusterers.EM
  Get debug mode
getDebug() - Method in class weka.datagenerators.ClusterGenerator
  Gets the debug flag.
getDebug() - Method in class weka.datagenerators.Generator
  Gets the debug flag.
getDebug() - Method in class weka.experiment.DatabaseUtils
  Gets whether there should be printed some debugging output to stderr or not
getDebug() - Method in class weka.filters.unsupervised.attribute.AddExpression
  Gets whether debug is set
getDebug() - Method in class weka.gui.streams.InstanceCounter
getDebug() - Method in class weka.gui.streams.InstanceJoiner
getDebug() - Method in class weka.gui.streams.InstanceLoader
getDebug() - Method in class weka.gui.streams.InstanceSavePanel
getDebug() - Method in class weka.gui.streams.InstanceTable
getDebug() - Method in class weka.gui.streams.InstanceViewer
getDecay() - Method in class weka.classifiers.functions.MultilayerPerceptron
getDefaultWeight() - Method in class weka.classifiers.functions.Winnow
  Get the value of defaultWeight.
getDelimiters() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Get the value of delimiters.
getDelta() - Method in class weka.associations.Apriori
  Get the value of delta.
getDelta() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
getDelta() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
getDensityBasedClusterer() - Method in class weka.filters.unsupervised.attribute.ClusterMembership
  Get the clusterer used by this filter
getDescendantPopulationSize() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
getDescendantPopulationSize() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
getDescription() - Method in class weka.gui.ExtensionFileFilter
  Gets the description of accepted files.
getDescription() - Method in class weka.gui.visualize.JComponentWriter
  returns the name of the writer, to display in the FileChooser.
getDescription() - Method in class weka.gui.visualize.JPEGWriter
  returns the name of the writer, to display in the FileChooser.
getDescription() - Method in class weka.gui.visualize.PostscriptWriter
  returns the name of the writer, to display in the FileChooser.
getDesignatedClass() - Method in class weka.classifiers.meta.ThresholdSelector
  Gets the method to determine which class value to optimize.
getDesiredSize() - Method in class weka.classifiers.meta.Decorate
  Gets the desired size of the committee.
getDesiredWeightOfInstancesPerInterval() - Method in class weka.filters.unsupervised.attribute.Discretize
  Get the DesiredWeightOfInstancesPerInterval value.
getDestination() - Static method in class weka.gui.experiment.ExperimenterDefaults
  returns the default destination
getDeviceConfiguration() - Method in class weka.gui.visualize.PostscriptGraphics
getDir() - Method in class weka.gui.Loader
  returns the dir prefix
getDirection() - Method in class weka.attributeSelection.BestFirst
  Get the search direction
getDiscretizer() - Method in class weka.classifiers.trees.j48.NBTreeNoSplit
  Return the discretizer used at this node
getDisplayedResultsets() - Method in class weka.experiment.PairedTTester
  Gets the indices of the the datasets that are displayed (if `null` then all are displayed).
getDisplayRules() - Method in class weka.classifiers.rules.DecisionTable
  Gets whether rules are being printed
getDistanceWeighting() - Method in class weka.classifiers.lazy.IBk
  Gets the distance weighting method used.
getDistMult() - Method in class weka.datagenerators.BIRCHCluster
  Gets the distance multiplier.
getDistribution() - Method in class weka.filters.unsupervised.attribute.RandomProjection
  Returns the current distribution that'll be used for calculating the random matrix
getDistributions() - Method in class weka.classifiers.bayes.BayesNet
  Get full set of estimators.
getDistributions(int) - Method in class weka.classifiers.rules.RuleStats
  Get the class distribution predicted by the rule in given position
getDistributionSpread() - Method in class weka.filters.supervised.instance.SpreadSubsample
  Gets the value for the distribution spread
getDocType() - Method in class weka.core.xml.XMLDocument
  returns the current DOCTYPE, can be `null`
getDocument() - Method in class weka.core.xml.XMLDocument
  returns the parsed DOM document
getDocument() - Method in class weka.core.xml.XMLOptions
  returns the parsed DOM document
getDontNormalize() - Method in class weka.classifiers.lazy.LWL
  Gets whether if the numeric attribute values are not to be normalized for calculating the distances.
getDoublePivot() - Method in class weka.core.matrix.LUDecomposition
  Return pivot permutation vector as a one-dimensional double array
getEditor() - Method in class weka.gui.PropertyDialog
  Gets the current property editor.
getEditorActive() - Method in class weka.gui.experiment.GeneratorPropertyIteratorPanel
  Returns true if the editor is currently in an active status---that is the array is active and able to be edited.
getElement(int, int) - Method in class weka.core.Matrix
  Deprecated. Returns the value of a cell in the matrix.
getEliminateColinearAttributes() - Method in class weka.classifiers.functions.LinearRegression
  Get the value of EliminateColinearAttributes.
getEntropicAutoBlend() - Method in class weka.classifiers.lazy.KStar
  Get whether entropic blending being used
getEntry(double) - Method in class weka.classifiers.lazy.kstar.KStarCache.CacheTable
  Returns the table entry to which the specified key is mapped in this hashtable.
getEps() - Method in class weka.classifiers.functions.SMOreg
  Get the value of eps.
getEpsilon() - Method in class weka.classifiers.functions.SMO
  Get the value of epsilon.
getEpsilon() - Method in class weka.classifiers.functions.SMOreg
  Get the value of epsilon.
getEpsilonParameter() - Method in class weka.attributeSelection.SVMAttributeEval
  Get the value of P used with SMO
getError() - Method in class weka.classifiers.BVDecompose
  Get the calculated error rate
getError() - Method in class weka.classifiers.BVDecomposeSegCVSub
  Get the calculated error rate
getErrorOnProbabilities() - Method in class weka.classifiers.functions.SimpleLogistic
  Get the value of errorOnProbabilities.
getErrorOnProbabilities() - Method in class weka.classifiers.trees.LMT
  Get the value of errorOnProbabilities.
getErrors() - Method in class weka.classifiers.trees.j48.NBTreeNoSplit
  Return the errors made by the naive bayes model at this node
getErrors() - Method in class weka.classifiers.trees.j48.NBTreeSplit
  Return the errors made by the naive bayes models arising from this split.
getEstimatedErrorsForLeaf() - Method in class weka.classifiers.rules.part.C45PruneableDecList
  Computes estimated errors for leaf.
getEstimator() - Method in class weka.classifiers.bayes.BayesNet
  Get the BayesNetEstimator used for calculating the CPTs
getEstimator() - Method in class weka.classifiers.functions.PaceRegression
  Gets the estimator
getEstimator(double) - Method in interface weka.estimators.ConditionalEstimator
  Get a probability estimator for a value
getEstimator(double) - Method in class weka.estimators.DDConditionalEstimator
  Get a probability estimator for a value
getEstimator(double) - Method in class weka.estimators.DKConditionalEstimator
  Get a probability estimator for a value
getEstimator(double) - Method in class weka.estimators.DNConditionalEstimator
  Get a probability estimator for a value
getEstimator(double) - Method in class weka.estimators.KDConditionalEstimator
  Get a probability estimator for a value
getEstimator(double) - Method in class weka.estimators.KKConditionalEstimator
  Get a probability estimator for a value
getEstimator(double) - Method in class weka.estimators.NDConditionalEstimator
  Get a probability estimator for a value
getEstimator(double) - Method in class weka.estimators.NNConditionalEstimator
  Get a probability estimator for a value
getEvaluationMode() - Method in class weka.classifiers.meta.ThresholdSelector
  Gets the evaluation mode used.
getEvaluator() - Method in class weka.classifiers.meta.AttributeSelectedClassifier
  Gets the attribute evaluator used
getEvaluator() - Method in class weka.filters.supervised.attribute.AttributeSelection
  Get the name of the attribute/subset evaluator
getEvalUsingTrainingData() - Method in class weka.attributeSelection.OneRAttributeEval
  Returns true if the training data is to be used for evaluation
getEventName() - Method in class weka.gui.beans.BeanConnection
  Returns the name of the event for this conncetion
getEventSetDescriptors() - Method in class weka.gui.beans.AbstractDataSinkBeanInfo
  Get the event set descriptors for this bean
getEventSetDescriptors() - Method in class weka.gui.beans.AbstractDataSourceBeanInfo
  Get the event set descriptors pertinent to data sources
getEventSetDescriptors() - Method in class weka.gui.beans.AbstractTestSetProducerBeanInfo
getEventSetDescriptors() - Method in class weka.gui.beans.AbstractTrainAndTestSetProducerBeanInfo
getEventSetDescriptors() - Method in class weka.gui.beans.AbstractTrainingSetProducerBeanInfo
  Returns event set descriptors for this type of bean
getEventSetDescriptors() - Method in class weka.gui.beans.AttributeSummarizerBeanInfo
  Get the event set descriptors for this bean
getEventSetDescriptors() - Method in class weka.gui.beans.ClassAssignerBeanInfo
  Returns the event set descriptors
getEventSetDescriptors() - Method in class weka.gui.beans.ClassifierBeanInfo
getEventSetDescriptors() - Method in class weka.gui.beans.ClassifierPerformanceEvaluatorBeanInfo
getEventSetDescriptors() - Method in class weka.gui.beans.ClassValuePickerBeanInfo
  Returns the event set descriptors
getEventSetDescriptors() - Method in class weka.gui.beans.ClustererBeanInfo
getEventSetDescriptors() - Method in class weka.gui.beans.ClustererPerformanceEvaluatorBeanInfo
getEventSetDescriptors() - Method in class weka.gui.beans.DataVisualizerBeanInfo
  Get the event set descriptors for this bean
getEventSetDescriptors() - Method in class weka.gui.beans.FilterBeanInfo
  Get the event set descriptors for this bean
getEventSetDescriptors() - Method in class weka.gui.beans.GraphViewerBeanInfo
  Get the event set descriptors for this bean
getEventSetDescriptors() - Method in class weka.gui.beans.IncrementalClassifierEvaluatorBeanInfo
  Get the event set descriptors for this bean
getEventSetDescriptors() - Method in class weka.gui.beans.ModelPerformanceChartBeanInfo
  Get the event set descriptors for this bean
getEventSetDescriptors() - Method in class weka.gui.beans.PredictionAppenderBeanInfo
  Get the event set descriptors pertinent to data sources
getEventSetDescriptors() - Method in class weka.gui.beans.ScatterPlotMatrixBeanInfo
  Get the event set descriptors for this bean
getEventSetDescriptors() - Method in class weka.gui.beans.StripChartBeanInfo
  Get the event set descriptors for this bean
getEventSetDescriptors() - Method in class weka.gui.beans.TextViewerBeanInfo
  Get the event set descriptors for this bean
getExclusive() - Method in class weka.classifiers.rules.ConjunctiveRule
getExecutionStatus() - Method in class weka.experiment.TaskStatusInfo
  Get the execution status of this Task.
getExitOnClose() - Method in class weka.gui.arffviewer.ArffViewer
  returns TRUE if a System.exit(0) is done on a close
getExitOnClose() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  returns TRUE if a System.exit(0) is done on a close
getExpectedFrequency() - Method in class weka.associations.tertius.Rule
  Get the expected frequency of counter-instances of this rule.
getExpectedNumber() - Method in class weka.associations.tertius.Rule
getExpectedResultsPerAverage() - Method in class weka.experiment.AveragingResultProducer
  Get the value of ExpectedResultsPerAverage.
getExperiment() - Method in class weka.experiment.RemoteExperimentSubTask
  Get the experiment for this sub task
getExperiment() - Method in class weka.gui.experiment.SetupModePanel
  Gets the currently configured experiment.
getExperiment() - Method in class weka.gui.experiment.SetupPanel
  Gets the currently configured experiment.
getExperiment() - Method in class weka.gui.experiment.SimpleSetupPanel
  Gets the currently configured experiment.
getExperimentType() - Static method in class weka.gui.experiment.ExperimenterDefaults
  returns the default experiment type
getExplicitPropsFile() - Method in class weka.gui.GenericPropertiesCreator
  returns TRUE, if a file is loaded and not the Utils class used for locating the props file.
getExponent() - Method in class weka.classifiers.functions.SMO
  Get the value of exponent.
getExponent() - Method in class weka.classifiers.functions.SMOreg
  Get the value of exponent.
getExponent() - Method in class weka.classifiers.functions.VotedPerceptron
  Get the value of exponent.
getExpression() - Method in class weka.filters.unsupervised.attribute.AddExpression
  Get the expression
getExtension() - Static method in class weka.gui.experiment.ExperimenterDefaults
  returns the default experiment extension
getExtension() - Method in class weka.gui.visualize.JComponentWriter
  returns the extension (incl.
getExtension() - Method in class weka.gui.visualize.JPEGWriter
  returns the extension (incl.
getExtension() - Method in class weka.gui.visualize.PostscriptWriter
  returns the extension (incl.
getFactory() - Method in class weka.core.xml.XMLDocument
  returns the DocumentBuilderFactory
getFallout() - Method in class weka.classifiers.evaluation.TwoClassStats
  Calculate the fallout.
getFalseNegative() - Method in class weka.classifiers.evaluation.TwoClassStats
  Gets the number of positive instances predicted as negative
getFalsePositive() - Method in class weka.classifiers.evaluation.TwoClassStats
  Gets the number of negative instances predicted as positive
getFalsePositiveRate() - Method in class weka.classifiers.evaluation.TwoClassStats
  Calculate the false positive rate.
getFastRegression() - Method in class weka.classifiers.trees.LMT
  Get the value of fastRegression.
getFeatureSpaceNormalization() - Method in class weka.classifiers.functions.SMO
  Check whether feature spaces is being normalized.
getFeatureSpaceNormalization() - Method in class weka.classifiers.functions.SMOreg
  Check whether feature spaces is being normalized.
getFile() - Method in class weka.gui.visualize.JComponentWriter
  returns the file being used for storing the output
getFileDescription() - Method in class weka.core.converters.AbstractFileSaver
  to be pverridden
getFileDescription() - Method in class weka.core.converters.ArffLoader
  Returns a description of the file type.
getFileDescription() - Method in class weka.core.converters.ArffSaver
  Returns a description of the file type.
getFileDescription() - Method in class weka.core.converters.C45Loader
  Returns a description of the file type.
getFileDescription() - Method in class weka.core.converters.C45Saver
  Returns a description of the file type.
getFileDescription() - Method in class weka.core.converters.CSVLoader
  Returns a description of the file type.
getFileDescription() - Method in class weka.core.converters.CSVSaver
  Returns a description of the file type.
getFileDescription() - Method in interface weka.core.converters.FileSourcedConverter
  Get a one line description of the type of file
getFileDescription() - Method in class weka.core.converters.SerializedInstancesLoader
  Returns a description of the file type.
getFileDescription() - Method in class weka.core.converters.SerializedInstancesSaver
  Returns a description of the file type.
getFileExtension() - Method in class weka.core.converters.AbstractFileSaver
  Gets ihe file extension.
getFileExtension() - Method in class weka.core.converters.AbstractSaver
  Default implementation throws an IOException.
getFileExtension() - Method in class weka.core.converters.ArffLoader
  Get the file extension used for arff files
getFileExtension() - Method in class weka.core.converters.C45Loader
  Get the file extension used for arff files
getFileExtension() - Method in class weka.core.converters.CSVLoader
  Get the file extension used for arff files
getFileExtension() - Method in interface weka.core.converters.FileSourcedConverter
  Get the file extension used for this type of file
getFileExtension() - Method in interface weka.core.converters.Saver
  Gets the file extension
getFileExtension() - Method in class weka.core.converters.SerializedInstancesLoader
  Get the file extension used for arff files
getFileName() - Method in class weka.classifiers.bayes.net.BIFReader
getFilename() - Method in class weka.gui.arffviewer.ArffPanel
  returns the filename
getFilename(int) - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  returns the filename of the specified panel
getFillWithMissing() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries
  Gets whether missing values should be used rather than removing instances where the translated value is not known (due to border effects).
getFilter() - Method in class weka.classifiers.meta.FilteredClassifier
  Gets the filter used.
getFilter() - Method in class weka.gui.beans.Filter
getFiltered(int) - Method in class weka.classifiers.rules.RuleStats
  Get the data after filtering the given rule
getFilterType() - Method in class weka.attributeSelection.SVMAttributeEval
  Get the filtering mode passed to SMO
getFilterType() - Method in class weka.classifiers.functions.SMO
  Gets how the training data will be transformed.
getFilterType() - Method in class weka.classifiers.functions.SMOreg
  Gets how the training data will be transformed.
getFindNumBins() - Method in class weka.filters.unsupervised.attribute.Discretize
  Get the value of FindNumBins.
getFindNumBins() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize
  Get the value of FindNumBins.
getFirst() - Method in class weka.associations.tertius.SimpleLinkedList
getFirstToken(StreamTokenizer) - Static method in class weka.core.converters.ConverterUtils
  Gets token, skipping empty lines.
getFirstValueIndex() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues
  Get the index of the first value used.
getFirstValueIndex() - Method in class weka.filters.unsupervised.attribute.SwapValues
  Get the index of the first value used.
getFlag(char, String[]) - Static method in class weka.core.Utils
  Checks if the given array contains the flag "-Char".
getFlag(String, String[]) - Static method in class weka.core.Utils
  Checks if the given array contains the flag "-String".
getFMeasure() - Method in class weka.classifiers.evaluation.TwoClassStats
  Calculate the F-Measure.
getFold() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds
  Gets the fold which is selected.
getFold() - Method in class weka.filters.unsupervised.instance.RemoveFolds
  Gets the fold which is selected.
getFoldColumn() - Method in class weka.experiment.PairedTTester
  Get the value of FoldColumn.
getFolds() - Method in class weka.attributeSelection.OneRAttributeEval
  Get the number of folds used for cross validation
getFolds() - Method in class weka.attributeSelection.WrapperSubsetEval
  Get the number of folds used for accuracy estimation
getFolds() - Method in class weka.classifiers.rules.ConjunctiveRule
getFolds() - Method in class weka.classifiers.rules.JRip
getFolds() - Method in class weka.classifiers.rules.Ridor
getFolds() - Method in class weka.gui.beans.CrossValidationFoldMaker
  Get the currently set number of folds
getFolds() - Static method in class weka.gui.experiment.ExperimenterDefaults
  returns the number of folds used for cross-validation
getFoldsType() - Method in class weka.attributeSelection.RaceSearch
  Get the xfold type
getFont() - Method in class weka.gui.visualize.PostscriptGraphics
  Get current font.
getFontMetrics(Font) - Method in class weka.gui.visualize.PostscriptGraphics
  Get Font metrics
getFontRenderContext() - Method in class weka.gui.visualize.PostscriptGraphics
  START overridden Graphics2D methods
getFPRate() - Method in class weka.associations.tertius.Rule
  Get the rate of False Positive instances of this rule.
getFrameTitle() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  returns the title (incl.
getFrequencyThreshold() - Method in class weka.associations.Tertius
  Get the value of frequencyThreshold.
getFunctionValue(int) - Method in class weka.classifiers.functions.pace.DiscreteFunction
  Gets a particular function value
getGamma() - Method in class weka.classifiers.functions.SMO
  Get the value of gamma.
getGamma() - Method in class weka.classifiers.functions.SMOreg
  Get the value of gamma.
getGCount(Node, int) - Static method in class weka.gui.treevisualizer.Node
  Recursively finds the number of visible groups of siblings there are.
getGenerateRanking() - Method in class weka.attributeSelection.GreedyStepwise
  Gets whether ranking has been requested.
getGenerateRanking() - Method in class weka.attributeSelection.RaceSearch
  Gets whether ranking has been requested.
getGenerateRanking() - Method in interface weka.attributeSelection.RankedOutputSearch
  Gets whether the user has opted to see a ranked list of attributes rather than the normal result of the search
getGenerateRanking() - Method in class weka.attributeSelection.Ranker
  This is a dummy method.
getGeneratorSamplesBase() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel
  Get the base used for computing the number of samples to obtain from each generator
getGlobalBlend() - Method in class weka.classifiers.lazy.KStar
  Get the value of the global blend parameter
getGlobalInfo(Object) - Static method in class weka.gui.beans.KnowledgeFlowApp
  Utility method for grabbing the global info help (if it exists) from an arbitrary object
getGlobalModel() - Method in class weka.classifiers.trees.j48.NBTreeSplit
  Return the global naive bayes model for this node
getGraphString() - Method in class weka.gui.beans.GraphEvent
  Return the dot string for the graph
getGraphTitle() - Method in class weka.gui.beans.GraphEvent
  Return the graph title
getGraphType() - Method in class weka.gui.beans.GraphEvent
  Return the graph type
getGridFlag() - Method in class weka.datagenerators.BIRCHCluster
  Gets the grid flag (option G).
getGridWidth() - Method in class weka.gui.beans.AttributeSummarizer
  Get the width of the grid of plots
getGroup() - Method in class weka.classifiers.rules.DecisionTable.Link
  Gets the group.
getGUI() - Method in class weka.classifiers.functions.MultilayerPerceptron
getH() - Method in class weka.core.matrix.QRDecomposition
  Return the Householder vectors
getHashtable(FastVector, int) - Static method in class weka.associations.ItemSet
  Return a hashtable filled with the given item sets.
getHashtable(FastVector, int) - Static method in class weka.associations.LabeledItemSet
  Return a hashtable filled with the given item sets.
getHeight() - Method in class weka.gui.beans.BeanInstance
  Gets the height of this bean
getHeight(Node, int) - Static method in class weka.gui.treevisualizer.Node
  Recursively finds the number of visible levels there are.
getHeuristicStop() - Method in class weka.classifiers.functions.SimpleLogistic
  Get the value of heuristicStop.
getHiddenLayers() - Method in class weka.classifiers.functions.MultilayerPerceptron
getHoldOutFile() - Method in class weka.attributeSelection.ClassifierSubsetEval
  Gets the file that holds hold out/test instances.
getHornClauses() - Method in class weka.associations.Tertius
  Get the value of hornClauses.
getIconPath() - Method in class weka.gui.beans.BeanVisual
  returns the path for the icon
getId() - Method in class weka.classifiers.functions.neural.NeuralConnection
getID() - Method in class weka.core.Tag
  Gets the numeric ID of the Tag.
getID() - Method in class weka.gui.streams.InstanceEvent
  Get the event type
getID() - Method in class weka.gui.treevisualizer.TreeDisplayEvent
getIDFTransform() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Sets whether if the word frequencies in a document should be transformed into:
  fij*log(num of Docs/num of Docs with word i)
  where fij is the frequency of word i in document(instance) j.
getIgnoredAttributeIndices() - Method in class weka.filters.unsupervised.attribute.AddCluster
  Gets ranges of attributes to be ignored.
getIgnoredAttributeIndices() - Method in class weka.filters.unsupervised.attribute.ClusterMembership
  Gets ranges of attributes to be ignored.
getImage(String, String) - Static method in class weka.gui.ComponentHelper
  returns the Image for a given directory and filename, NULL if not successful
getImage(String) - Static method in class weka.gui.ComponentHelper
  returns the Image for a given filename, NULL if not successful
getImageIcon(String, String) - Static method in class weka.gui.ComponentHelper
  returns the ImageIcon for a given filename and directory, NULL if not successful
getImageIcon(String) - Static method in class weka.gui.ComponentHelper
  returns the ImageIcon for a given filename, NULL if not successful
getImagEigenvalues() - Method in class weka.core.matrix.EigenvalueDecomposition
  Return the imaginary parts of the eigenvalues
getIncludeClass() - Method in class weka.core.InstanceComparator
  returns TRUE if the class is included in the comparison
getIndex() - Method in class weka.associations.tertius.Predicate
getIndex() - Method in class weka.core.SingleIndex
  Gets the selected index
getInitAsNaiveBayes() - Method in class weka.classifiers.bayes.net.search.global.HillClimber
  Method declaration
getInitAsNaiveBayes() - Method in class weka.classifiers.bayes.net.search.global.K2
  Method declaration
getInitAsNaiveBayes() - Method in class weka.classifiers.bayes.net.search.local.HillClimber
  Method declaration
getInitAsNaiveBayes() - Method in class weka.classifiers.bayes.net.search.local.K2
  Method declaration
getInitial() - Method in class weka.core.Memory
  returns the initial size of the JVM
getInitialDatasetsDirectory() - Static method in class weka.gui.experiment.ExperimenterDefaults
  returns the initial directory for the datasets (if empty, it returns the user's home directory)
getInputFilename() - Method in class weka.gui.GenericPropertiesCreator
  returns the name of the input file
getInputNums() - Method in class weka.classifiers.functions.neural.NeuralConnection
  Use this to get easy access to the input numbers.
getInputOrder() - Method in class weka.datagenerators.BIRCHCluster
  Gets the input order.
getInputProperties() - Method in class weka.gui.GenericPropertiesCreator
  returns the input properties object (template containing the packages)
getInputs() - Method in class weka.classifiers.functions.neural.NeuralConnection
  Use this to get easy access to the inputs.
getInputs() - Method in class weka.gui.beans.MetaBean
getInputStream(String, String) - Static method in class weka.gui.Loader
  returns an InputStream for the given dir and filename, can be NULL if it fails
getInputStream(String) - Method in class weka.gui.Loader
  returns an InputStream for the given filename, can be NULL if it fails
getInstalledLookAndFeels() - Static method in class weka.gui.LookAndFeel
  returns an array with the classnames of all the installed LnFs
getInstance() - Method in class weka.gui.beans.InstanceEvent
  Get the instance
getInstanceIndex(int) - Method in class weka.classifiers.lazy.LBR.Indexes
  Returns the boolean value at the specified index in the Instance Index array
getInstanceRange() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries
  Gets the number of instances forward to translate values between.
getInstances() - Method in class weka.core.converters.AbstractSaver
  Gets instances that should be stored.
getInstances() - Method in class weka.experiment.PairedTTester
  Get the value of Instances.
getInstances() - Method in class weka.gui.arffviewer.ArffPanel
  returns the instances of the panel, if none then NULL
getInstances() - Method in class weka.gui.arffviewer.ArffTableModel
  returns the data
getInstances() - Method in class weka.gui.arffviewer.ArffTableSorter
  returns the data
getInstances() - Method in class weka.gui.boundaryvisualizer.BoundaryVisualizer
  Get the training instances
getInstances() - Method in class weka.gui.explorer.PreprocessPanel
  Gets the working set of instances.
getInstances() - Method in class weka.gui.SetInstancesPanel
  Gets the set of instances currently held by the panel
getInstances() - Method in class weka.gui.treevisualizer.Node
  This will return the Instances object related to this node.
getInstances() - Method in class weka.gui.ViewerDialog
  returns the currently displayed instances
getInstances() - Method in class weka.gui.visualize.VisualizePanel
  Get the master plot's instances
getInstances1() - Method in class weka.gui.visualize.VisualizePanelEvent
getInstances2() - Method in class weka.gui.visualize.VisualizePanelEvent
getInstancesIndices() - Method in class weka.filters.unsupervised.instance.RemoveRange
  Gets ranges of instances selected.
getInstNums() - Method in class weka.datagenerators.BIRCHCluster
  Gets the upper and lower boundary for instances per cluster.
getIntercept() - Method in class weka.classifiers.functions.SimpleLinearRegression
  Returns the intercept of the function.
getInvert() - Method in class weka.core.Range
  Gets whether the range sense is inverted, i.e.
getInvert() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified
  Get whether selection is inverted.
getInvertSelection() - Method in class weka.filters.supervised.attribute.Discretize
  Gets whether the supplied columns are to be removed or kept
getInvertSelection() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds
  Gets if selection is to be inverted.
getInvertSelection() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries
  Get whether the supplied columns are to be removed or kept
getInvertSelection() - Method in class weka.filters.unsupervised.attribute.Copy
  Get whether the supplied columns are to be removed or kept
getInvertSelection() - Method in class weka.filters.unsupervised.attribute.Discretize
  Gets whether the supplied columns are to be removed or kept
getInvertSelection() - Method in class weka.filters.unsupervised.attribute.NominalToBinary
  Gets whether the supplied columns are to be removed or kept
getInvertSelection() - Method in class weka.filters.unsupervised.attribute.NumericTransform
  Get whether the supplied columns are to be transformed or not
getInvertSelection() - Method in class weka.filters.unsupervised.attribute.Remove
  Get whether the supplied columns are to be removed or kept
getInvertSelection() - Method in class weka.filters.unsupervised.attribute.RemoveType
  Get whether the supplied columns are to be removed or kept
getInvertSelection() - Method in class weka.filters.unsupervised.instance.RemoveFolds
  Gets if selection is to be inverted.
getInvertSelection() - Method in class weka.filters.unsupervised.instance.RemovePercentage
  Gets if selection is to be inverted.
getInvertSelection() - Method in class weka.filters.unsupervised.instance.RemoveRange
  Gets if selection is to be inverted.
getInvertSelection() - Method in class weka.filters.unsupervised.instance.RemoveWithValues
  Get whether the supplied columns are to be removed or kept
getJavaInitializationString() - Method in class weka.gui.CostMatrixEditor
  Returns the Java code that generates an object the same as the one being edited.
getJavaInitializationString() - Method in class weka.gui.FileEditor
  Returns a representation of the current property value as java source.
getJavaInitializationString() - Method in class weka.gui.GenericArrayEditor
  Supposedly returns an initialization string to create a classifier identical to the current one, including it's state, but this doesn't appear possible given that the initialization string isn't supposed to contain multiple statements.
getJavaInitializationString() - Method in class weka.gui.GenericObjectEditor
  Supposedly returns an initialization string to create a Object identical to the current one, including it's state, but this doesn't appear possible given that the initialization string isn't supposed to contain multiple statements.
getJavaInitializationString() - Method in class weka.gui.SelectedTagEditor
  Returns a description of the property value as java source.
getJavaInitializationString() - Method in class weka.gui.SimpleDateFormatEditor
  Returns the Java code that generates an object the same as the one being edited.
getJTable() - Method in class weka.gui.JTableHelper
  returns the JTable
getKernelBandwidth() - Method in class weka.gui.boundaryvisualizer.KDDataGenerator
  Get the kernel bandwidth
getKey() - Method in class weka.experiment.ClassifierSplitEvaluator
  Gets the key describing the current SplitEvaluator.
getKey() - Method in class weka.experiment.RegressionSplitEvaluator
  Gets the key describing the current SplitEvaluator.
getKey() - Method in interface weka.experiment.SplitEvaluator
  Gets the key describing the current SplitEvaluator.
getKeyFieldName() - Method in class weka.experiment.AveragingResultProducer
  Get the value of KeyFieldName.
getKeyNames() - Method in class weka.experiment.AveragingResultProducer
  Gets the names of each of the columns produced for a single run.
getKeyNames() - Method in class weka.experiment.ClassifierSplitEvaluator
  Gets the names of each of the key columns produced for a single run.
getKeyNames() - Method in class weka.experiment.CrossValidationResultProducer
  Gets the names of each of the columns produced for a single run.
getKeyNames() - Method in class weka.experiment.DatabaseResultProducer
  Gets the names of each of the columns produced for a single run.
getKeyNames() - Method in class weka.experiment.LearningRateResultProducer
  Gets the names of each of the columns produced for a single run.
getKeyNames() - Method in class weka.experiment.RandomSplitResultProducer
  Gets the names of each of the columns produced for a single run.
getKeyNames() - Method in class weka.experiment.RegressionSplitEvaluator
  Gets the names of each of the key columns produced for a single run.
getKeyNames() - Method in interface weka.experiment.ResultProducer
  Gets the names of each of the key columns produced for a single run.
getKeyNames() - Method in interface weka.experiment.SplitEvaluator
  Gets the names of each of the key columns produced for a single run.
getKeys() - Method in class weka.core.converters.DatabaseLoader
  Gets the key columns' name
getKeyTypes() - Method in class weka.experiment.AveragingResultProducer
  Gets the data types of each of the columns produced for a single run.
getKeyTypes() - Method in class weka.experiment.ClassifierSplitEvaluator
  Gets the data types of each of the key columns produced for a single run.
getKeyTypes() - Method in class weka.experiment.CrossValidationResultProducer
  Gets the data types of each of the columns produced for a single run.
getKeyTypes() - Method in class weka.experiment.DatabaseResultProducer
  Gets the data types of each of the columns produced for a single run.
getKeyTypes() - Method in class weka.experiment.LearningRateResultProducer
  Gets the data types of each of the columns produced for a single run.
getKeyTypes() - Method in class weka.experiment.RandomSplitResultProducer
  Gets the data types of each of the columns produced for a single run.
getKeyTypes() - Method in class weka.experiment.RegressionSplitEvaluator
  Gets the data types of each of the key columns produced for a single run.
getKeyTypes() - Method in interface weka.experiment.ResultProducer
  Gets the data types of each of the key columns produced for a single run.
getKeyTypes() - Method in interface weka.experiment.SplitEvaluator
  Gets the data types of each of the key columns produced for a single run.
getKNN() - Method in class weka.classifiers.lazy.IBk
  Gets the number of neighbours the learner will use.
getKNN() - Method in class weka.classifiers.lazy.LWL
  Gets the number of neighbours used for kernel bandwidth setting.
getKValue() - Method in class weka.classifiers.trees.RandomTree
  Get the value of K.
getKWBias() - Method in class weka.classifiers.BVDecomposeSegCVSub
  Get the calculated bias squared according to the Kohavi and Wolpert definition
getKWSigma() - Method in class weka.classifiers.BVDecomposeSegCVSub
  Get the calculated sigma according to the Kohavi and Wolpert definition
getKWVariance() - Method in class weka.classifiers.BVDecomposeSegCVSub
  Get the calculated variance according to the Kohavi and Wolpert definition
getL() - Method in class weka.core.matrix.CholeskyDecomposition
  Return triangular factor.
getL() - Method in class weka.core.Matrix
  Deprecated. Returns the L part of the matrix.
getL() - Method in class weka.core.matrix.LUDecomposition
  Return lower triangular factor
getLabel() - Method in class weka.gui.treevisualizer.Edge
  Get the value of label.
getLabel() - Method in class weka.gui.treevisualizer.Node
  Get the value of label.
getLast() - Method in class weka.associations.tertius.SimpleLinkedList
getLastLiteral() - Method in class weka.associations.tertius.LiteralSet
  Give the last literal added to this set.
getLearningRate() - Method in class weka.classifiers.functions.MultilayerPerceptron
getLegendText() - Method in class weka.gui.beans.ChartEvent
  Get the legend text vector
getLevel() - Method in class weka.gui.HierarchyPropertyParser
  Get the level of current node.
getLikelihoodThreshold() - Method in class weka.classifiers.meta.LogitBoost
  Get the value of Precision.
getLine(int) - Method in class weka.gui.treevisualizer.Edge
  Returns line number n
getLine(int) - Method in class weka.gui.treevisualizer.Node
  Returns the text String for the specfied line.
getLinkAt(int) - Method in class weka.attributeSelection.BestFirst.LinkedList2
  returns the element (Link) at a specific index from the list.
getLinkAt(int) - Method in class weka.classifiers.rules.DecisionTable.LinkedList
  Returns the element (Link) at a specific index from the list.
getList() - Method in class weka.gui.ResultHistoryPanel
  Gets the JList used by the results list
getListCellRendererComponent(JList, Object, int, boolean, boolean) - Method in class weka.gui.experiment.AlgorithmListPanel.ObjectCellRenderer
getLiteral(int) - Method in class weka.associations.tertius.Predicate
getLNorm() - Method in class weka.filters.unsupervised.instance.Normalize
  Get the L Norm used.
getLoader() - Method in class weka.gui.beans.Loader
  Get the loader
getLocallyPredictive() - Method in class weka.attributeSelection.CfsSubsetEval
  Return true if including locally predictive attributes
getLogLikelihood() - Method in class weka.clusterers.ClusterEvaluation
  Return the log likelihood corresponding to the most recent set of instances clustered.
getLookupCacheSize() - Method in class weka.attributeSelection.BestFirst
  Return the maximum size of the evaluated subset cache (expressed as a multiplier for the number of attributes in a data set.
getLower() - Method in class weka.gui.experiment.RunNumberPanel
  Gets the current lower run number.
getLowerBoundMinSupport() - Method in class weka.associations.Apriori
  Get the value of lowerBoundMinSupport.
getLowerCaseTokens() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Gets whether if the tokens are to be downcased or not.
getLowerNumericBound() - Method in class weka.core.Attribute
  Returns the lower bound of a numeric attribute.
getLowerOrderTerms() - Method in class weka.classifiers.functions.SMO
  Check whether lower-order terms are being used.
getLowerOrderTerms() - Method in class weka.classifiers.functions.SMOreg
  Check whether lower-order terms are being used.
getLowerSize() - Method in class weka.experiment.LearningRateResultProducer
  Get the value of LowerSize.
getM5RootNode() - Method in class weka.classifiers.trees.m5.M5Base
getM5RootNode() - Method in class weka.classifiers.trees.m5.Rule
getMainPanel() - Method in class weka.gui.arffviewer.ArffViewer
  returns the main panel
getMajorityClass() - Method in class weka.classifiers.rules.Ridor
getMakeBinary() - Method in class weka.filters.supervised.attribute.Discretize
  Gets whether binary attributes should be made for discretized ones.
getMakeBinary() - Method in class weka.filters.unsupervised.attribute.Discretize
  Gets whether binary attributes should be made for discretized ones.
getMarkovBlanketClassifier() - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
getMarkovBlanketClassifier() - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
getMasterPlot() - Method in class weka.gui.visualize.Plot2D
  Get the master plot
getMatchMissingValues() - Method in class weka.filters.unsupervised.instance.RemoveWithValues
  Gets whether missing values are counted as a match.
getMatrix(int, int, int, int) - Method in class weka.classifiers.functions.pace.Matrix
  Get a submatrix.
getMatrix(int[], int[]) - Method in class weka.classifiers.functions.pace.Matrix
  Get a submatrix.
getMatrix(int, int, int[]) - Method in class weka.classifiers.functions.pace.Matrix
  Get a submatrix.
getMatrix(int[], int, int) - Method in class weka.classifiers.functions.pace.Matrix
  Get a submatrix.
getMatrix(int, int, int, int) - Method in class weka.core.matrix.Matrix
  Get a submatrix.
getMatrix(int[], int[]) - Method in class weka.core.matrix.Matrix
  Get a submatrix.
getMatrix(int, int, int[]) - Method in class weka.core.matrix.Matrix
  Get a submatrix.
getMatrix(int[], int, int) - Method in class weka.core.matrix.Matrix
  Get a submatrix.
getMax() - Method in class weka.core.Memory
  returns the maximum amount of memory that can be assigned
getMax() - Method in class weka.gui.beans.ChartEvent
  Get the max y value
getMaxBoostingIterations() - Method in class weka.classifiers.functions.SimpleLogistic
  Get the value of maxBoostingIterations.
getMaxC() - Method in class weka.gui.visualize.Plot2D
  Return the current max value of the colouring attribute
getMaxCardinality() - Method in class weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm
getMaxChunkSize() - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost
  Get the maximum chunk size
getMaxCost(int) - Method in class weka.classifiers.CostMatrix
  Gets the maximum cost for a particular class value.
getMaxCount() - Method in class weka.filters.supervised.instance.SpreadSubsample
  Gets the value for the max count
getMaxDepth() - Method in class weka.classifiers.trees.REPTree
  Get the value of MaxDepth.
getMaxGenerations() - Method in class weka.attributeSelection.GeneticSearch
  get the number of generations
getMaximumAttributeNames() - Method in class weka.attributeSelection.PrincipalComponents
  Gets maximum number of attributes to include in transformed attribute names.
getMaximumVariancePercentageAllowed() - Method in class weka.filters.unsupervised.attribute.RemoveUseless
  Gets the maximum variance attributes are allowed to have before they are deleted by the filter.
getMaxInstNum() - Method in class weka.datagenerators.BIRCHCluster
  Gets the upper boundary for instances per cluster.
getMaxIterations() - Method in class weka.classifiers.trees.lmt.LogisticBase
  Returns the maxIterations parameter.
getMaxIterations() - Method in class weka.clusterers.EM
  Get the maximum number of iterations
getMaxIterations() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified
  Gets the maximum number of cleansing iterations performed
getMaxIts() - Method in class weka.classifiers.functions.Logistic
  Get the value of MaxIts.
getMaxIts() - Method in class weka.classifiers.functions.RBFNetwork
  Get the value of MaxIts.
getMaxK() - Method in class weka.classifiers.functions.VotedPerceptron
  Get the value of maxK.
getMaxNrOfParents() - Method in class weka.classifiers.bayes.net.search.global.HillClimber
  Method declaration
getMaxNrOfParents() - Method in class weka.classifiers.bayes.net.search.global.K2
  Method declaration
getMaxNrOfParents() - Method in class weka.classifiers.bayes.net.search.local.HillClimber
  Method declaration
getMaxNrOfParents() - Method in class weka.classifiers.bayes.net.search.local.K2
  Method declaration
getMaxPlots() - Method in class weka.gui.beans.AttributeSummarizer
  Get the number of plots to display
getMaxRadius() - Method in class weka.datagenerators.BIRCHCluster
  Gets the upper boundary for the radiuses of the clusters.
getMaxRuleSize() - Method in class weka.datagenerators.RDG1
  Gets the maximum number of tests in rules.
getMaxSetNumber() - Method in class weka.gui.beans.BatchClassifierEvent
  Get the maximum set number (ie the total number of training and testing sets in the series).
getMaxSetNumber() - Method in class weka.gui.beans.BatchClustererEvent
  Get the maximum set number (ie the total number of training and testing sets in the series).
getMaxSetNumber() - Method in class weka.gui.beans.TestSetEvent
  Get the maximum set number
getMaxSetNumber() - Method in class weka.gui.beans.TrainingSetEvent
  Get the maximum set number
getMaxStale() - Method in class weka.classifiers.rules.DecisionTable
  Gets the number of non improving decision tables
getMaxX() - Method in class weka.gui.visualize.Plot2D
  Return the current max value of the attribute plotted on the x axis
getMaxY() - Method in class weka.gui.visualize.Plot2D
  Return the current max value of the attribute plotted on the y axis
getMeanPrec() - Method in class weka.experiment.PairedTTester
  Gets the precision used for printing the mean
getMeanPrec() - Method in class weka.gui.experiment.OutputFormatDialog
  Gets the precision used for printing the mean
getMeanPrecision() - Static method in class weka.gui.experiment.ExperimenterDefaults
  returns the default precision for the mean
getMeanSquared() - Method in class weka.classifiers.lazy.IBk
  Gets whether the mean squared error is used rather than mean absolute error when doing cross-validation.
getMeasure(String) - Method in class weka.classifiers.bayes.BayesNet
  Returns the value of the named measure
getMeasure(String) - Method in class weka.classifiers.functions.SimpleLogistic
  Returns the value of the named measure
getMeasure(String) - Method in class weka.classifiers.meta.AdditiveRegression
  Returns the value of the named measure
getMeasure(String) - Method in class weka.classifiers.meta.AttributeSelectedClassifier
  Returns the value of the named measure
getMeasure(String) - Method in class weka.classifiers.meta.Bagging
  Returns the value of the named measure.
getMeasure(String) - Method in class weka.classifiers.rules.DecisionTable
  Returns the value of the named measure
getMeasure(String) - Method in class weka.classifiers.rules.JRip
  Returns the value of the named measure
getMeasure(String) - Method in class weka.classifiers.rules.PART
  Returns the value of the named measure
getMeasure(String) - Method in class weka.classifiers.rules.Ridor
  Returns the value of the named measure
getMeasure(String) - Method in class weka.classifiers.trees.ADTree
  Returns the value of the named measure.
getMeasure(String) - Method in class weka.classifiers.trees.J48
  Returns the value of the named measure
getMeasure(String) - Method in class weka.classifiers.trees.LMT
  Returns the value of the named measure
getMeasure(String) - Method in class weka.classifiers.trees.m5.M5Base
  Returns the value of the named measure
getMeasure(String) - Method in class weka.classifiers.trees.NBTree
  Returns the value of the named measure
getMeasure(String) - Method in class weka.classifiers.trees.RandomForest
  Returns the value of the named measure.
getMeasure(String) - Method in class weka.classifiers.trees.REPTree
  Returns the value of the named measure.
getMeasure(String) - Method in interface weka.core.AdditionalMeasureProducer
  Returns the value of the named measure
getMeasure(String) - Method in class weka.experiment.AveragingResultProducer
  Returns the value of the named measure
getMeasure(String) - Method in class weka.experiment.ClassifierSplitEvaluator
  Returns the value of the named measure
getMeasure(String) - Method in class weka.experiment.CrossValidationResultProducer
  Returns the value of the named measure
getMeasure(String) - Method in class weka.experiment.DatabaseResultProducer
  Returns the value of the named measure
getMeasure(String) - Method in class weka.experiment.LearningRateResultProducer
  Returns the value of the named measure
getMeasure(String) - Method in class weka.experiment.RandomSplitResultProducer
  Returns the value of the named measure
getMeasure(String) - Method in class weka.experiment.RegressionSplitEvaluator
  Returns the value of the named measure
getMenu() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  returns the menu bar to be added in a frame
getMerit() - Method in class weka.classifiers.rules.DecisionTable.Link
  Gets the merit.
getMetaClassifier() - Method in class weka.classifiers.meta.Stacking
  Gets the meta classifier.
getMetadata() - Method in class weka.core.Attribute
  Returns the properties supplied for this attribute.
getMetaData() - Method in class weka.core.converters.DatabaseConnection
  Gets meta data for the database connection object.
getMethod() - Method in class weka.classifiers.functions.neural.NeuralNode
getMethod() - Method in class weka.classifiers.meta.MultiClassClassifier
  Gets the method used.
getMethodName() - Method in class weka.filters.unsupervised.attribute.NumericTransform
  Get the transformation method.
getMetricType() - Method in class weka.associations.Apriori
  Get the metric type
getMidPoints() - Method in class weka.associations.PriorEstimation
  returns an ordered array of all mid points
getMin() - Method in class weka.gui.beans.ChartEvent
  Get the min y value
getMinBucketSize() - Method in class weka.classifiers.rules.OneR
  Get the value of minBucketSize.
getMinC() - Method in class weka.gui.visualize.Plot2D
  Return the current min value of the colouring attribute
getMinChunkSize() - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost
  Get the minimum chunk size
getMinFunction() - Method in class weka.core.Optimization
  Get the minimal function value
getMinimizeExpectedCost() - Method in class weka.classifiers.meta.CostSensitiveClassifier
  Gets the value of MinimizeExpectedCost.
getMinimumBucketSize() - Method in class weka.attributeSelection.OneRAttributeEval
  Get the minimum bucket size used by oneR
getMinInstNum() - Method in class weka.datagenerators.BIRCHCluster
  Gets the lower boundary for instances per cluster.
getMinMetric() - Method in class weka.associations.Apriori
  Get the value of minConfidence.
getMinNo() - Method in class weka.classifiers.rules.ConjunctiveRule
getMinNo() - Method in class weka.classifiers.rules.JRip
getMinNo() - Method in class weka.classifiers.rules.Ridor
getMinNum() - Method in class weka.classifiers.trees.RandomTree
  Get the value of MinNum.
getMinNum() - Method in class weka.classifiers.trees.REPTree
  Get the value of MinNum.
getMinNumInstances() - Method in class weka.classifiers.trees.LMT
  Get the value of minNumInstances.
getMinNumInstances() - Method in class weka.classifiers.trees.m5.M5Base
  Get the minimum number of instances to allow at a leaf node
getMinNumInstances() - Method in class weka.classifiers.trees.m5.Rule
  Get the minimum number of instances to allow at a leaf node
getMinNumInstances() - Method in class weka.classifiers.trees.m5.RuleNode
  Get the minimum number of instances to allow at a leaf node
getMinNumObj() - Method in class weka.classifiers.rules.PART
  Get the value of minNumObj.
getMinNumObj() - Method in class weka.classifiers.trees.J48
  Get the value of minNumObj.
getMinRadius() - Method in class weka.datagenerators.BIRCHCluster
  Gets the lower boundary for the radiuses of the clusters.
getMinRuleSize() - Method in class weka.datagenerators.RDG1
  Gets the minimum number of tests in rules.
getMinStdDev() - Method in class weka.classifiers.functions.RBFNetwork
  Get the MinStdDev value.
getMinStdDev() - Method in class weka.clusterers.EM
  Get the minimum allowable standard deviation.
getMinStdDev() - Method in class weka.clusterers.MakeDensityBasedClusterer
  Get the minimum allowable standard deviation.
getMinVarianceProp() - Method in class weka.classifiers.trees.REPTree
  Get the value of MinVarianceProp.
getMinX() - Method in class weka.gui.visualize.Plot2D
  Return the current min value of the attribute plotted on the x axis
getMinY() - Method in class weka.gui.visualize.Plot2D
  Return the current min value of the attribute plotted on the y axis
getMissingMerge() - Method in class weka.attributeSelection.ChiSquaredAttributeEval
  get whether missing values are being distributed or not
getMissingMerge() - Method in class weka.attributeSelection.GainRatioAttributeEval
  get whether missing values are being distributed or not
getMissingMerge() - Method in class weka.attributeSelection.InfoGainAttributeEval
  get whether missing values are being distributed or not
getMissingMerge() - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval
  get whether missing values are being distributed or not
getMissingMode() - Method in class weka.classifiers.lazy.KStar
  Gets the method to use for handling missing values.
getMissingSeperate() - Method in class weka.attributeSelection.CfsSubsetEval
  Return true is missing is treated as a seperate value
getMissingValues() - Method in class weka.associations.Tertius
  Get the value of missingValues.
getMixingDistribution() - Method in class weka.classifiers.functions.pace.MixtureDistribution
  Gets the mixing distribution
getModel() - Method in class weka.classifiers.trees.m5.RuleNode
  Get the linear model at this node
getModel() - Method in class weka.gui.TableMap
getModelParameters() - Method in class weka.classifiers.trees.lmt.LMTNode
  Returns a string describing the number of LogitBoost iterations performed at this node, the total number of LogitBoost iterations performed (including iterations at higher levels in the tree), and the number of training examples at this node.
getModelValueAt(int, int) - Method in class weka.gui.arffviewer.ArffTableSorter
  returns the value at the given position
getModelValueAt(int, int) - Method in class weka.gui.TableSorter
  access to the unsorted values
getModifyHeader() - Method in class weka.filters.unsupervised.instance.RemoveWithValues
  Gets whether the header will be modified when selecting on nominal attributes.
getMomentum() - Method in class weka.classifiers.functions.MultilayerPerceptron
getMutationProb() - Method in class weka.attributeSelection.GeneticSearch
  get the probability of mutation
getNaiveBayesModel() - Method in class weka.classifiers.trees.j48.NBTreeNoSplit
  Get the naive bayes model at this node
getName() - Method in class weka.classifiers.bayes.BayesNet
  get name of the Bayes network
getName() - Method in class weka.filters.unsupervised.attribute.AddExpression
  Returns the name of the new attribute
getName() - Method in class weka.gui.visualize.VisualizePanel
  Returns the name associated with this plot.
getNameAtIndex(int) - Method in class weka.gui.ResultHistoryPanel
  Gets the name of theitem in the list at the specified index
getNamedBuffer(String) - Method in class weka.gui.ResultHistoryPanel
  Gets the named buffer
getNamedObject(String) - Method in class weka.gui.ResultHistoryPanel
  Get the named object from the list
getNegation() - Method in class weka.associations.Tertius
  Get the value of negation.
getNegation() - Method in class weka.associations.tertius.Literal
getNext(int) - Method in class weka.classifiers.functions.supportVector.SMOset
  Gets the next element in the set.
getNextInstance(Instances) - Method in class weka.core.converters.AbstractLoader
getNextInstance(Instances) - Method in class weka.core.converters.ArffLoader
  Read the data set incrementally---get the next instance in the data set or returns null if there are no more instances to get.
getNextInstance(Instances) - Method in class weka.core.converters.C45Loader
  Read the data set incrementally---get the next instance in the data set or returns null if there are no more instances to get.
getNextInstance(Instances) - Method in class weka.core.converters.CSVLoader
  CSVLoader is unable to process a data set incrementally.
getNextInstance(Instances) - Method in class weka.core.converters.DatabaseLoader
  Read the data set incrementally---get the next instance in the data set or returns null if there are no more instances to get.
getNextInstance(Instances) - Method in interface weka.core.converters.Loader
  Read the data set incrementally---get the next instance in the data set or returns null if there are no more instances to get.
getNextInstance(Instances) - Method in class weka.core.converters.SerializedInstancesLoader
  Read the data set incrementally---get the next instance in the data set or returns null if there are no more instances to get.
getNode(String) - Method in class weka.classifiers.bayes.net.BIFReader
  getNode finds the index of the node with name sNodeName and throws an exception if no such node can be found.
getNodeName(int) - Method in class weka.classifiers.bayes.BayesNet
  get name of a node in the Bayes network
getNodes() - Method in class weka.classifiers.trees.lmt.LMTNode
  Return a list of all inner nodes in the tree
getNodes(Vector) - Method in class weka.classifiers.trees.lmt.LMTNode
  Fills a list with all inner nodes in the tree
getNodeValue(int, int) - Method in class weka.classifiers.bayes.BayesNet
  get name of a particular value of a node
getNoiseRate() - Method in class weka.datagenerators.BIRCHCluster
  Gets the percentage of noise set.
getNoiseThreshold() - Method in class weka.associations.Tertius
  Get the value of noiseThreshold.
getNominalIndices() - Method in class weka.filters.unsupervised.instance.RemoveWithValues
  Get the set of nominal value indices that will be used for selection
getNominalLabels() - Method in class weka.filters.unsupervised.attribute.Add
  Get the list of labels for nominal attribute creation
getNominalToBinaryFilter() - Method in class weka.classifiers.functions.MultilayerPerceptron
getNoNormalization() - Method in class weka.classifiers.lazy.IBk
  Gets whether normalization is turned off.
getNoPruning() - Method in class weka.classifiers.trees.REPTree
  Get the value of NoPruning.
getNorm() - Method in class weka.filters.unsupervised.instance.Normalize
  Get the instance's Norm.
getNormalize() - Method in class weka.attributeSelection.PrincipalComponents
  Gets whether or not input data is to be normalized
getNormalizeAttributes() - Method in class weka.classifiers.functions.MultilayerPerceptron
getNormalizeDocLength() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Gets whether if the word frequencies for a document (instance) should be normalized or not.
getNormalizeNumericClass() - Method in class weka.classifiers.functions.MultilayerPerceptron
getNormalizeWordWeights() - Method in class weka.classifiers.bayes.ComplementNaiveBayes
  Returns true if the word weights for each class are to be normalized
getNot() - Method in class weka.datagenerators.Test
  Negates the test.
getNotes() - Method in class weka.experiment.Experiment
  Get the user notes.
getNPointPrecision(Instances, int) - Static method in class weka.classifiers.evaluation.ThresholdCurve
  Calculates the n point precision result, which is the precision averaged over n evenly spaced (w.r.t recall) samples of the curve.
getNrOfNodes() - Method in class weka.classifiers.bayes.BayesNet
  get number of nodes in the Bayes network
getNrOfParents(int) - Method in class weka.classifiers.bayes.BayesNet
  get number of parents of a node in the network structure
getNrOfParents() - Method in class weka.classifiers.bayes.net.ParentSet
  returns number of parents
getNumAntds() - Method in class weka.classifiers.rules.ConjunctiveRule
getNumAttemptsOfGeneOption() - Method in class weka.classifiers.rules.NNge
  Gets the number of attempts for generalisation.
getNumAttributes() - Method in class weka.classifiers.lazy.LBR.Indexes
  Returns the number of attributes in the dataset
getNumAttributes() - Method in class weka.datagenerators.ClusterGenerator
  Gets the number of attributes that should be produced.
getNumAttributes() - Method in class weka.datagenerators.Generator
  Gets the number of attributes that should be produced.
getNumAttributesSet() - Method in class weka.classifiers.lazy.LBR.Indexes
  Returns the number of attributes "in use"
getNumberLiterals() - Method in class weka.associations.Tertius
  Get the value of numberLiterals.
getNumberOfAttributes() - Method in class weka.filters.unsupervised.attribute.RandomProjection
  Gets the current number of attributes (dimensionality) to which the data will be reduced to.
getNumBins() - Method in class weka.classifiers.meta.RegressionByDiscretization
  Gets the number of bins numeric attributes will be divided into
getNumBoostingIterations() - Method in class weka.classifiers.functions.SimpleLogistic
  Get the value of numBoostingIterations.
getNumBoostingIterations() - Method in class weka.classifiers.trees.LMT
  Get the value of numBoostingIterations.
getNumClasses() - Method in class weka.datagenerators.Generator
  Gets the number of classes the dataset should have.
getNumClusters() - Method in class weka.classifiers.functions.RBFNetwork
  Return the number of clusters to generate.
getNumClusters() - Method in class weka.clusterers.ClusterEvaluation
  Return the number of clusters found for the most recent call to evaluateClusterer
getNumClusters() - Method in class weka.clusterers.EM
  Get the number of clusters
getNumClusters() - Method in class weka.clusterers.FarthestFirst
  gets the number of clusters to generate
getNumClusters() - Method in class weka.clusterers.SimpleKMeans
  gets the number of clusters to generate
getNumClusters() - Method in class weka.datagenerators.ClusterGenerator
  Gets the number of clusters the dataset should have.
getNumCycles() - Method in class weka.datagenerators.BIRCHCluster
  Gets the number of cycles.
getNumDatasets() - Method in class weka.experiment.PairedTTester
  Gets the number of datasets in the resultsets
getNumDisplayedResultsets() - Method in class weka.experiment.PairedTTester
  Gets the number of displayed resultsets in the data.
getNumeric() - Method in class weka.filters.unsupervised.attribute.MakeIndicator
  Check if new attribute is to be numeric.
getNumExamples() - Method in class weka.datagenerators.Generator
  Gets the number of examples, given by option.
getNumExamplesAct() - Method in class weka.datagenerators.ClusterGenerator
  Gets the number of examples the dataset should have.
getNumExamplesAct() - Method in class weka.datagenerators.Generator
  Gets the number of examples the dataset should have.
getNumFeatures() - Method in class weka.classifiers.trees.RandomForest
  Get the number of features used in random selection.
getNumFoldersMIOption() - Method in class weka.classifiers.rules.NNge
  Gets the number of folder for mutual information.
getNumFolds() - Method in class weka.classifiers.functions.SMO
  Get the value of numFolds.
getNumFolds() - Method in class weka.classifiers.meta.CVParameterSelection
  Gets the number of folds for the cross-validation.
getNumFolds() - Method in class weka.classifiers.meta.LogitBoost
  Get the value of NumFolds.
getNumFolds() - Method in class weka.classifiers.meta.MultiScheme
  Gets the number of folds for cross-validation.
getNumFolds() - Method in class weka.classifiers.meta.Stacking
  Gets the number of folds for the cross-validation.
getNumFolds() - Method in class weka.classifiers.rules.PART
  Get the value of numFolds.
getNumFolds() - Method in class weka.classifiers.trees.J48
  Get the value of numFolds.
getNumFolds() - Method in class weka.classifiers.trees.REPTree
  Get the value of NumFolds.
getNumFolds() - Method in class weka.experiment.CrossValidationResultProducer
  Get the value of NumFolds.
getNumFolds() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds
  Gets the number of folds in which dataset is to be split into.
getNumFolds() - Method in class weka.filters.unsupervised.instance.RemoveFolds
  Gets the number of folds in which dataset is to be split into.
getNumFolds() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified
  Gets the number of cross-validation folds used by the filter.
getNumGeneratingModels() - Method in interface weka.gui.boundaryvisualizer.DataGenerator
  Returns the number of generating models used by this DataGenerator
getNumGeneratingModels() - Method in class weka.gui.boundaryvisualizer.KDDataGenerator
  Return the number of kernels (there is one per training instance)
getNumInnerNodes() - Method in class weka.classifiers.trees.lmt.LMTNode
  Method to count the number of inner nodes in the tree
getNumInputs() - Method in class weka.classifiers.functions.neural.NeuralConnection
getNumInstances() - Method in class weka.classifiers.CheckClassifier
  Gets the current number of instances to use for the datasets.
getNumInstances() - Method in class weka.classifiers.lazy.LBR.Indexes
  Returns the number of instances in the dataset
getNumInstances() - Method in class weka.classifiers.trees.m5.RuleNode
  Return the number of instances that reach this node.
getNumInstancesSet() - Method in class weka.classifiers.lazy.LBR.Indexes
  Returns the number of instances "in use"
getNumIrrelevant() - Method in class weka.datagenerators.RDG1
  Gets the number of irrelevant attributes.
getNumIterations() - Method in class weka.classifiers.functions.VotedPerceptron
  Get the value of NumIterations.
getNumIterations() - Method in class weka.classifiers.functions.Winnow
  Get the value of numIterations.
getNumIterations() - Method in class weka.classifiers.IteratedSingleClassifierEnhancer
  Gets the number of bagging iterations
getNumIterations() - Method in class weka.classifiers.meta.MetaCost
  Gets the number of bagging iterations
getNumLeaves() - Method in class weka.classifiers.trees.lmt.LMTNode
  Returns the number of leaves in the tree.
getNumNeighbours() - Method in class weka.attributeSelection.ReliefFAttributeEval
  Get the number of nearest neighbours
getNumNumeric() - Method in class weka.datagenerators.RDG1
  Gets the number of numerical attributes.
getNumOfBoostingIterations() - Method in class weka.classifiers.trees.ADTree
  Gets the number of boosting iterations.
getNumOfBranches() - Method in class weka.classifiers.trees.adtree.Splitter
  Gets the number of branches of the split.
getNumOfBranches() - Method in class weka.classifiers.trees.adtree.TwoWayNominalSplit
  Gets the number of branches of the split.
getNumOfBranches() - Method in class weka.classifiers.trees.adtree.TwoWayNumericSplit
  Gets the number of branches of the split.
getNumOutputs() - Method in class weka.classifiers.functions.neural.NeuralConnection
getNumRegressions() - Method in class weka.classifiers.functions.SimpleLogistic
  Get the number of LogitBoost iterations performed (= the number of regression functions fit by LogitBoost).
getNumRegressions() - Method in class weka.classifiers.trees.lmt.LogisticBase
  The number of LogitBoost iterations performed (= the number of simple regression functions fit).
getNumResultsets() - Method in class weka.experiment.PairedTTester
  Gets the number of resultsets in the data.
getNumRules() - Method in class weka.associations.Apriori
  Get the value of numRules.
getNumRules() - Method in class weka.associations.PredictiveApriori
  Get the value of the number of required rules.
getNumRuns() - Method in class weka.classifiers.meta.LogitBoost
  Get the value of NumRuns.
getNumSamplesPerRegion() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel
  Get the number of points to sample from a region (fixed dimensions).
getNumSubCmtys() - Method in class weka.classifiers.meta.MultiBoostAB
  Get the number of sub committees to use
getNumSymbols() - Method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes
  Gets the number of symbols this estimator operates with
getNumSymbols() - Method in class weka.estimators.DiscreteEstimator
  Gets the number of symbols this estimator operates with
getNumToSelect() - Method in class weka.attributeSelection.GreedyStepwise
  Gets the number of attributes to be retained.
getNumToSelect() - Method in class weka.attributeSelection.RaceSearch
  Gets the number of attributes to be retained.
getNumToSelect() - Method in interface weka.attributeSelection.RankedOutputSearch
  Gets the user specified number of attributes to be retained.
getNumToSelect() - Method in class weka.attributeSelection.Ranker
  Gets the number of attributes to be retained.
getNumTraining() - Method in class weka.classifiers.lazy.IBk
  Get the number of training instances the classifier is currently using
getNumTrees() - Method in class weka.classifiers.trees.RandomForest
  Get the value of numTrees.
getNumXValFolds() - Method in class weka.classifiers.meta.ThresholdSelector
  Get the number of folds used for cross-validation.
getObject() - Method in class weka.core.SerializedObject
  Returns a serialized object.
getObservedFrequency() - Method in class weka.associations.tertius.Rule
  Get the observed frequency of counter-instances of this rule in the dataset.
getObservedNumber() - Method in class weka.associations.tertius.Rule
  Get the observed number of counter-instances of this rule in the dataset.
getOnDemandDirectory() - Method in class weka.classifiers.meta.CostSensitiveClassifier
  Returns the directory that will be searched for cost files when loading on demand.
getOnDemandDirectory() - Method in class weka.classifiers.meta.MetaCost
  Returns the directory that will be searched for cost files when loading on demand.
getOnDemandDirectory() - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator
  Returns the directory that will be searched for cost files when loading on demand.
getOnlyAlphabeticTokens() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Gets whether if the tokens are to be formed only from contiguous alphabetic sequences.
getOptimistic() - Method in class weka.associations.tertius.Rule
  Get the optimistic estimate of the confirmation obtained by refining this rule.
getOptimizations() - Method in class weka.classifiers.rules.JRip
getOption(char, String[]) - Static method in class weka.core.Utils
  Gets an option indicated by a flag "-Char" from the given array of strings.
getOption(String, String[]) - Static method in class weka.core.Utils
  Gets an option indicated by a flag "-String" from the given array of strings.
getOptions() - Method in class weka.associations.Apriori
  Gets the current settings of the Apriori object.
getOptions() - Method in class weka.associations.PredictiveApriori
  Gets the current settings of the PredictiveApriori object.
getOptions() - Method in class weka.associations.Tertius
  Gets the current settings of the Tertius object.
getOptions() - Method in class weka.attributeSelection.BestFirst
  Gets the current settings of BestFirst.
getOptions() - Method in class weka.attributeSelection.CfsSubsetEval
  Gets the current settings of CfsSubsetEval
getOptions() - Method in class weka.attributeSelection.ChiSquaredAttributeEval
  Gets the current settings of WrapperSubsetEval.
getOptions() - Method in class weka.attributeSelection.ClassifierSubsetEval
  Gets the current settings of ClassifierSubsetEval
getOptions() - Method in class weka.attributeSelection.ExhaustiveSearch
  Gets the current settings of RandomSearch.
getOptions() - Method in class weka.attributeSelection.GainRatioAttributeEval
  Gets the current settings of WrapperSubsetEval.
getOptions() - Method in class weka.attributeSelection.GeneticSearch
  Gets the current settings of ReliefFAttributeEval.
getOptions() - Method in class weka.attributeSelection.GreedyStepwise
  Gets the current settings of ReliefFAttributeEval.
getOptions() - Method in class weka.attributeSelection.InfoGainAttributeEval
  Gets the current settings of WrapperSubsetEval.
getOptions() - Method in class weka.attributeSelection.OneRAttributeEval
getOptions() - Method in class weka.attributeSelection.PrincipalComponents
  Gets the current settings of PrincipalComponents
getOptions() - Method in class weka.attributeSelection.RaceSearch
  Gets the current settings of BestFirst.
getOptions() - Method in class weka.attributeSelection.RandomSearch
  Gets the current settings of RandomSearch.
getOptions() - Method in class weka.attributeSelection.Ranker
  Gets the current settings of ReliefFAttributeEval.
getOptions() - Method in class weka.attributeSelection.RankSearch
  Gets the current settings of WrapperSubsetEval.
getOptions() - Method in class weka.attributeSelection.ReliefFAttributeEval
  Gets the current settings of ReliefFAttributeEval.
getOptions() - Method in class weka.attributeSelection.SVMAttributeEval
  Gets the current settings of SVMAttributeEval
getOptions() - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval
  Gets the current settings of WrapperSubsetEval.
getOptions() - Method in class weka.attributeSelection.WrapperSubsetEval
  Gets the current settings of WrapperSubsetEval.
getOptions() - Method in class weka.classifiers.bayes.AODE
  Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.bayes.BayesNet
  Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.bayes.ComplementNaiveBayes
  Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.bayes.NaiveBayes
  Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.bayes.net.BayesNetGenerator
  Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator
  Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.bayes.net.estimate.BMAEstimator
  Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator
  Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.bayes.net.search.fixed.FromFile
  Gets the current settings of the search algorithm.
getOptions() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
  Gets the current settings of the search algorithm.
getOptions() - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
  Gets the current settings of the search algorithm.
getOptions() - Method in class weka.classifiers.bayes.net.search.global.HillClimber
  Gets the current settings of the search algorithm.
getOptions() - Method in class weka.classifiers.bayes.net.search.global.K2
  Gets the current settings of the search algorithm.
getOptions() - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber
  Gets the current settings of the search algorithm.
getOptions() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
  Gets the current settings of the search algorithm.
getOptions() - Method in class weka.classifiers.bayes.net.search.global.TabuSearch
  Gets the current settings of the search algorithm.
getOptions() - Method in class weka.classifiers.bayes.net.search.global.TAN
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
  Gets the current settings of the search algorithm.
getOptions() - Method in class weka.classifiers.bayes.net.search.local.HillClimber
  Gets the current settings of the search algorithm.
getOptions() - Method in class weka.classifiers.bayes.net.search.local.K2
  Gets the current settings of the search algorithm.
getOptions() - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
getOptions() - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber
  Gets the current settings of the search algorithm.
getOptions() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
  Gets the current settings of the search algorithm.
getOptions() - Method in class weka.classifiers.bayes.net.search.local.TabuSearch
  Gets the current settings of the search algorithm.
getOptions() - Method in class weka.classifiers.bayes.net.search.local.TAN
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.bayes.net.search.SearchAlgorithm
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.BVDecompose
  Gets the current settings of the CheckClassifier.
getOptions() - Method in class weka.classifiers.BVDecomposeSegCVSub
  Gets the current settings of the CheckClassifier.
getOptions() - Method in class weka.classifiers.CheckClassifier
  Gets the current settings of the CheckClassifier.
getOptions() - Method in class weka.classifiers.Classifier
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.functions.LeastMedSq
  Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.classifiers.functions.LinearRegression
  Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.functions.Logistic
  Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.functions.MultilayerPerceptron
  Gets the current settings of NeuralNet.
getOptions() - Method in class weka.classifiers.functions.PaceRegression
  Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.functions.RBFNetwork
  Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.functions.SimpleLogistic
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.functions.SMO
  Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.functions.SMOreg
  Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.functions.VotedPerceptron
  Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.functions.Winnow
  Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.IteratedSingleClassifierEnhancer
  Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.lazy.IBk
  Gets the current settings of IBk.
getOptions() - Method in class weka.classifiers.lazy.KStar
  Gets the current settings of K*.
getOptions() - Method in class weka.classifiers.lazy.LWL
  Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.meta.AdaBoostM1
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.AdditiveRegression
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.AttributeSelectedClassifier
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.Bagging
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.CostSensitiveClassifier
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.CVParameterSelection
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.Decorate
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.FilteredClassifier
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.LogitBoost
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.MetaCost
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.MultiBoostAB
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.MultiClassClassifier
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.MultiScheme
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.OrdinalClassClassifier
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.RegressionByDiscretization
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.Stacking
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.ThresholdSelector
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.misc.VFI
  Gets the current settings of VFI
getOptions() - Method in class weka.classifiers.MultipleClassifiersCombiner
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.RandomizableClassifier
  Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.RandomizableIteratedSingleClassifierEnhancer
  Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.RandomizableMultipleClassifiersCombiner
  Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.RandomizableSingleClassifierEnhancer
  Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.rules.ConjunctiveRule
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.rules.DecisionTable
  Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.rules.JRip
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.rules.NNge
  Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.classifiers.rules.OneR
  Gets the current settings of the OneR classifier.
getOptions() - Method in class weka.classifiers.rules.PART
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.rules.Ridor
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.SingleClassifierEnhancer
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.trees.ADTree
  Gets the current settings of ADTree.
getOptions() - Method in class weka.classifiers.trees.J48
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.trees.LMT
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.trees.m5.M5Base
  Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.trees.M5P
  Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.trees.RandomForest
  Gets the current settings of the forest.
getOptions() - Method in class weka.classifiers.trees.RandomTree
  Gets options from this classifier.
getOptions() - Method in class weka.classifiers.trees.REPTree
  Gets options from this classifier.
getOptions() - Method in class weka.clusterers.Cobweb
  Gets the current settings of Cobweb.
getOptions() - Method in class weka.clusterers.EM
  Gets the current settings of EM.
getOptions() - Method in class weka.clusterers.FarthestFirst
  Gets the current settings of FarthestFirst
getOptions() - Method in class weka.clusterers.MakeDensityBasedClusterer
  Gets the current settings of the clusterer.
getOptions() - Method in class weka.clusterers.SimpleKMeans
  Gets the current settings of SimpleKMeans
getOptions() - Method in class weka.core.converters.AbstractFileSaver
  Gets the current settings of the Saver object.
getOptions() - Method in class weka.core.converters.C45Saver
  Gets the current settings of the C45Saver object.
getOptions() - Method in class weka.core.converters.DatabaseLoader
  Gets the setting
getOptions() - Method in class weka.core.converters.DatabaseSaver
  Gets the setting
getOptions() - Method in interface weka.core.OptionHandler
  Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.datagenerators.BIRCHCluster
  Gets the current settings of the datagenerator BIRCHCluster.
getOptions() - Method in class weka.datagenerators.RDG1
  Gets the current settings of the datagenerator RDG1.
getOptions() - Method in class weka.experiment.AveragingResultProducer
  Gets the current settings of the result producer.
getOptions() - Method in class weka.experiment.ClassifierSplitEvaluator
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.experiment.CrossValidationResultProducer
  Gets the current settings of the result producer.
getOptions() - Method in class weka.experiment.CSVResultListener
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.experiment.DatabaseResultProducer
  Gets the current settings of the result producer.
getOptions() - Method in class weka.experiment.Experiment
  Gets the current settings of the experiment iterator.
getOptions() - Method in class weka.experiment.InstanceQuery
  Gets the current settings of InstanceQuery
getOptions() - Method in class weka.experiment.LearningRateResultProducer
  Gets the current settings of the result producer.
getOptions() - Method in class weka.experiment.PairedTTester
  Gets current settings of the PairedTTester.
getOptions() - Method in class weka.experiment.RandomSplitResultProducer
  Gets the current settings of the result producer.
getOptions() - Method in class weka.experiment.RegressionSplitEvaluator
  Gets the current settings of the Classifier.
getOptions() - Method in class weka.filters.supervised.attribute.AttributeSelection
  Gets the current settings for the attribute selection (search, evaluator) etc.
getOptions() - Method in class weka.filters.supervised.attribute.ClassOrder
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.supervised.attribute.Discretize
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.supervised.attribute.NominalToBinary
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.supervised.instance.Resample
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.supervised.instance.SpreadSubsample
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.Add
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.AddCluster
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.AddExpression
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.AddNoise
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat
  {@inheritDoc
getOptions() - Method in class weka.filters.unsupervised.attribute.ClusterMembership
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.Copy
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.Discretize
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.FirstOrder
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.MakeIndicator
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.NominalToBinary
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.NumericTransform
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.RandomProjection
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.Remove
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.RemoveType
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.RemoveUseless
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.StringToNominal
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.SwapValues
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.Normalize
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.Randomize
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.RemoveFolds
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.RemovePercentage
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.RemoveRange
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.RemoveWithValues
  Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.Resample
  Gets the current settings of the filter.
getOrderedFlag() - Method in class weka.datagenerators.BIRCHCluster
  Gets the ordered flag (option O).
getOriginalCoords() - Method in class weka.gui.beans.MetaBean
  returns the vector containing the original coordinates (instances of class Point) for the inputs
getOutput() - Method in class weka.datagenerators.ClusterGenerator
  Gets the print writer.
getOutput() - Method in class weka.datagenerators.Generator
  Gets the print writer.
getOutputFile() - Method in class weka.experiment.CrossValidationResultProducer
  Get the value of OutputFile.
getOutputFile() - Method in class weka.experiment.CSVResultListener
  Get the value of OutputFile.
getOutputFile() - Method in class weka.experiment.RandomSplitResultProducer
  Get the value of OutputFile.
getOutputFilename() - Method in class weka.gui.GenericPropertiesCreator
  returns the name of the output file
getOutputFormat() - Method in class weka.filters.Filter
  Gets the format of the output instances.
getOutputFormat() - Method in class weka.filters.unsupervised.attribute.PotentialClassIgnorer
  Gets the format of the output instances.
getOutputItemSets() - Method in class weka.associations.Apriori
  Gets whether itemsets are output as well
getOutputNums() - Method in class weka.classifiers.functions.neural.NeuralConnection
  Use this to get easy access to the output numbers.
getOutputProperties() - Method in class weka.gui.GenericPropertiesCreator
  returns the output properties object (structure like the template, but filled with classes instead of packages)
getOutputs() - Method in class weka.classifiers.functions.neural.NeuralConnection
  Use this to get easy access to the outputs.
getOutputs() - Method in class weka.gui.beans.MetaBean
getOutputWordCounts() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Gets whether output instances contain 0 or 1 indicating word presence, or word counts.
getP() - Method in class weka.classifiers.BVDecomposeSegCVSub
  Get the proportion of instances that are common between two training sets.
getPaint() - Method in class weka.gui.visualize.PostscriptGraphics
getPanel(int) - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  returns the specified panel, `null` if index is out of bounds
getPanelCount() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  returns the number of panels currently open
getParent(int, int) - Method in class weka.classifiers.bayes.BayesNet
  get node index of a parent of a node in the network structure
getParent(int) - Method in class weka.classifiers.bayes.net.ParentSet
  returns index parent of parent specified by index
getParent(int) - Method in class weka.gui.treevisualizer.Node
  Get the parent edge.
getParentCardinality(int) - Method in class weka.classifiers.bayes.BayesNet
  get number of values the collection of parents of a node can take
getParentSet(int) - Method in class weka.classifiers.bayes.BayesNet
  get the parent set of a node
getParentSets() - Method in class weka.classifiers.bayes.BayesNet
  Get full set of parent sets.
getParts() - Method in class weka.associations.tertius.IndividualInstance
getPassword() - Method in class weka.experiment.DatabaseUtils
  Get the database password
getPassword() - Method in class weka.gui.DatabaseConnectionDialog
  Returns password from dialog
getPath() - Method in class weka.gui.PropertySelectorDialog
  Gets the path of property nodes to the selected property.
getPattern() - Method in class weka.datagenerators.BIRCHCluster
  Gets the pattern type.
getPercent() - Method in class weka.filters.unsupervised.attribute.AddNoise
  Gets the size of noise data as a percentage of the original set.
getPercent() - Method in class weka.filters.unsupervised.attribute.RandomProjection
  Gets the percent the attributes (dimensions) of the data will be reduced to
getPercentage() - Method in class weka.filters.unsupervised.instance.RemovePercentage
  Gets the percentage of instances to select.
getPercentCompleted() - Method in class weka.gui.boundaryvisualizer.RemoteResult
  Return the progress for this row
getPercentThreshold() - Method in class weka.attributeSelection.SVMAttributeEval
  Get the threshold below which percentage elimination reverts to constant elimination.
getPercentToEliminatePerIteration() - Method in class weka.attributeSelection.SVMAttributeEval
  Get the percentage rate of attribute elimination per iteration
getPivot() - Method in class weka.core.matrix.LUDecomposition
  Return pivot permutation vector
getPlainColumnName(int) - Method in class weka.gui.arffviewer.ArffTable
  returns the basically the attribute name of the column and not the HTML column name via getColumnName(int)
getPlotInstances() - Method in class weka.gui.visualize.PlotData2D
  Returns the instances for this plot
getPlotName() - Method in class weka.gui.visualize.PlotData2D
  Get the name of this plot
getPlots() - Method in class weka.gui.visualize.Plot2D
  Return the list of plots
getPlotTrainingData() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel
  Returns true if training data is to be superimposed
getPointValue(int) - Method in class weka.classifiers.functions.pace.DiscreteFunction
  Gets a particular point value
getPopulationSize() - Method in class weka.attributeSelection.GeneticSearch
  get the size of the population
getPopulationSize() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
getPopulationSize() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
getPostProcessor() - Method in class weka.classifiers.CheckClassifier
  returns the current PostProcessor, can be null
getPrecision() - Method in class weka.classifiers.evaluation.TwoClassStats
  Calculate the precision.
getPredicate() - Method in class weka.associations.tertius.Literal
getPrediction(Classifier, Instance) - Method in class weka.classifiers.evaluation.EvaluationUtils
  Generate a single prediction for a test instance given the pre-trained classifier.
getPredTargetColumn() - Method in class weka.experiment.ClassifierSplitEvaluator
getProbabilities() - Method in class weka.gui.boundaryvisualizer.RemoteResult
  Return the probability distributions for this row in the visualization
getProbability(int, int, int) - Method in class weka.classifiers.bayes.BayesNet
  get particular probability of the conditional probability distribtion of a node given its parents.
getProbability(double) - Method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes
  Get a probability estimate for a value
getProbability(double, double) - Method in interface weka.estimators.ConditionalEstimator
  Get a probability for a value conditional on another value
getProbability(double, double) - Method in class weka.estimators.DDConditionalEstimator
  Get a probability estimate for a value
getProbability(double) - Method in class weka.estimators.DiscreteEstimator
  Get a probability estimate for a value
getProbability(double, double) - Method in class weka.estimators.DKConditionalEstimator
  Get a probability estimate for a value
getProbability(double, double) - Method in class weka.estimators.DNConditionalEstimator
  Get a probability estimate for a value
getProbability(double) - Method in interface weka.estimators.Estimator
  Get a probability estimate for a value.
getProbability(double, double) - Method in class weka.estimators.KDConditionalEstimator
  Get a probability estimate for a value
getProbability(double) - Method in class weka.estimators.KernelEstimator
  Get a probability estimate for a value.
getProbability(double, double) - Method in class weka.estimators.KKConditionalEstimator
  Get a probability estimate for a value
getProbability(double) - Method in class weka.estimators.MahalanobisEstimator
  Get a probability estimate for a value
getProbability(double, double) - Method in class weka.estimators.NDConditionalEstimator
  Get a probability estimate for a value
getProbability(double, double) - Method in class weka.estimators.NNConditionalEstimator
  Get a probability estimate for a value
getProbability(double) - Method in class weka.estimators.NormalEstimator
  Get a probability estimate for a value
getProbability(double) - Method in class weka.estimators.PoissonEstimator
  Get a probability estimate for a value
getProduceCSV() - Method in class weka.experiment.PairedTTester
  Get whether csv is output
getProduceCSV() - Method in class weka.gui.experiment.OutputFormatDialog
  Get whether csv is output
getProduceLatex() - Method in class weka.experiment.PairedTTester
  Get whether latex is output
getProduceLatex() - Method in class weka.gui.experiment.OutputFormatDialog
  Get whether latex is output
getProgressBar() - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine
  Returns a handle to the progressBar of this LayoutEngine.
getProgressBar() - Method in interface weka.gui.graphvisualizer.LayoutEngine
  This method returns the progress bar for the LayoutEngine, which shows the progress of the layout process, if it takes a while to layout the graph
getProperties() - Static method in class weka.gui.experiment.ExperimenterDefaults
  returns the associated properties file
getPropertyArray() - Method in class weka.experiment.Experiment
  Gets the array of values to set the custom property to.
getPropertyArrayLength() - Method in class weka.experiment.Experiment
  Gets the number of custom iterator values that have been defined for the experiment.
getPropertyArrayValue(int) - Method in class weka.experiment.Experiment
  Gets a specified value from the custom property iterator array.
getPropertyDescriptors() - Method in class weka.gui.beans.ClassAssignerBeanInfo
  Returns the property descriptors
getPropertyDescriptors() - Method in class weka.gui.beans.ClassValuePickerBeanInfo
  Returns the property descriptors
getPropertyDescriptors() - Method in class weka.gui.beans.CrossValidationFoldMakerBeanInfo
  Return the property descriptors for this bean
getPropertyDescriptors() - Method in class weka.gui.beans.PredictionAppenderBeanInfo
  Return the property descriptors for this bean
getPropertyDescriptors() - Method in class weka.gui.beans.StripChartBeanInfo
  Get the property descriptors for this bean
getPropertyDescriptors() - Method in class weka.gui.beans.TrainTestSplitMakerBeanInfo
  Get the property descriptors for this bean
getPropertyPath() - Method in class weka.experiment.Experiment
  Gets the path of properties taken to get to the custom property to iterate over.
getPruningType() - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost
  Get the pruning type
getQ() - Method in class weka.core.matrix.QRDecomposition
  Generate and return the (economy-sized) orthogonal factor
getQuality() - Method in class weka.gui.visualize.JPEGWriter
  returns the quality the JPEG will be stored in
getQuery() - Method in class weka.core.converters.DatabaseLoader
  Gets the query to execute against the database
getQuery() - Method in class weka.experiment.InstanceQuery
  Get the query to execute against the database
getR() - Method in class weka.core.matrix.QRDecomposition
  Return the upper triangular factor
getRaceType() - Method in class weka.attributeSelection.RaceSearch
  Get the race type
getRadiuses() - Method in class weka.datagenerators.BIRCHCluster
  Gets the upper and lower boundary for the radius of the clusters.
getRandom() - Method in class weka.datagenerators.BIRCHCluster
  Gets the random generator.
getRandom() - Method in class weka.datagenerators.RDG1
  Gets the random generator.
getRandomizeData() - Method in class weka.experiment.RandomSplitResultProducer
  Get if dataset is to be randomized
getRandomNumberGenerator(long) - Method in class weka.core.Instances
  Returns a random number generator.
getRandomOrder() - Method in class weka.classifiers.bayes.net.search.global.K2
  Get random order flag
getRandomOrder() - Method in class weka.classifiers.bayes.net.search.local.K2
  Get random order flag
getRandomSeed() - Method in class weka.classifiers.functions.LeastMedSq
  get the seed for the random number generator
getRandomSeed() - Method in class weka.classifiers.functions.SMO
  Get the value of randomSeed.
getRandomSeed() - Method in class weka.classifiers.trees.ADTree
  Gets random seed for a random walk.
getRandomSeed() - Method in class weka.filters.supervised.instance.Resample
  Gets the random number seed.
getRandomSeed() - Method in class weka.filters.supervised.instance.SpreadSubsample
  Gets the random number seed.
getRandomSeed() - Method in class weka.filters.unsupervised.attribute.AddNoise
  Gets the random number seed.
getRandomSeed() - Method in class weka.filters.unsupervised.attribute.RandomProjection
  Gets the random seed of the random number generator
getRandomSeed() - Method in class weka.filters.unsupervised.instance.Randomize
  Get the random number generator seed value.
getRandomSeed() - Method in class weka.filters.unsupervised.instance.Resample
  Gets the random number seed.
getRandomWidthFactor() - Method in class weka.classifiers.meta.MultiClassClassifier
  Gets the multiplier when generating random codes.
getRangeCorrection() - Method in class weka.classifiers.meta.ThresholdSelector
  Gets the confidence range correction mode used.
getRanges() - Method in class weka.core.Range
  Gets the string representing the selected range of values
getRawOutput() - Method in class weka.experiment.CrossValidationResultProducer
  Get if raw split evaluator output is to be saved
getRawOutput() - Method in class weka.experiment.RandomSplitResultProducer
  Get if raw split evaluator output is to be saved
getRawResultOutput() - Method in class weka.experiment.ClassifierSplitEvaluator
  Gets the raw output from the classifier
getRawResultOutput() - Method in class weka.experiment.RegressionSplitEvaluator
  Gets the raw output from the classifier
getRawResultOutput() - Method in interface weka.experiment.SplitEvaluator
  Returns the raw output for the most recent call to getResult.
getReadable() - Method in class weka.core.Tag
  Gets the string description of the Tag.
getReader(String, String) - Static method in class weka.gui.Loader
  returns a Reader for the given filename and dir, can be NULL if it fails
getReader(String) - Method in class weka.gui.Loader
  returns a Reader for the given filename, can be NULL if it fails
getRealEigenvalues() - Method in class weka.core.matrix.EigenvalueDecomposition
  Return the real parts of the eigenvalues
getRecall() - Method in class weka.classifiers.evaluation.TwoClassStats
  Calculate the recall.
getReducedErrorPruning() - Method in class weka.classifiers.rules.PART
  Get the value of reducedErrorPruning.
getReducedErrorPruning() - Method in class weka.classifiers.trees.J48
  Get the value of reducedErrorPruning.
getRefer() - Method in class weka.gui.treevisualizer.Node
  Get the value of refer.
getRefreshFreq() - Method in class weka.gui.beans.StripChart
  Get the refresh frequency
getRegressionTree() - Method in class weka.classifiers.trees.m5.Rule
  Get the value of regressionTree.
getRegressionTree() - Method in class weka.classifiers.trees.m5.RuleNode
  Get the value of regressionTree.
getRelationForTableName() - Method in class weka.core.converters.DatabaseSaver
  Gets whether or not the relation name is used as name of the table
getRelationName() - Method in class weka.datagenerators.ClusterGenerator
  Gets the relation name the dataset should have.
getRelationName() - Method in class weka.datagenerators.Generator
  Gets the relation name the dataset should have.
getRemoteHosts() - Method in class weka.experiment.RemoteExperiment
  Get the list of remote host names
getRemoveAllMissingCols() - Method in class weka.associations.Apriori
  Returns whether columns containing all missing values are to be removed
getRenderingHint(RenderingHints.Key) - Method in class weka.gui.visualize.PostscriptGraphics
getRenderingHints() - Method in class weka.gui.visualize.PostscriptGraphics
getRepeatLiterals() - Method in class weka.associations.Tertius
  Get the value of repeatLiterals.
getRepetitions() - Static method in class weka.gui.experiment.ExperimenterDefaults
  returns the number of repetitions to use
getReplaceMissingValues() - Method in class weka.filters.unsupervised.attribute.RandomProjection
  Gets the current setting for using ReplaceMissingValues filter
getReportFrequency() - Method in class weka.attributeSelection.GeneticSearch
  get how often repports are generated
getReset() - Method in class weka.classifiers.functions.MultilayerPerceptron
getReset() - Method in class weka.gui.beans.ChartEvent
  get the value of the reset flag
getResult(Instances, Instances) - Method in class weka.experiment.ClassifierSplitEvaluator
  Gets the results for the supplied train and test datasets.
getResult(Instances, Instances) - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator
  Gets the results for the supplied train and test datasets.
getResult(Instances, Instances) - Method in class weka.experiment.RegressionSplitEvaluator
  Gets the results for the supplied train and test datasets.
getResult(Instances, Instances) - Method in interface weka.experiment.SplitEvaluator
  Gets the results for the supplied train and test datasets.
getResult() - Method in class weka.gui.experiment.OutputFormatDialog
  the result from the last display of the dialog, the same is returned from `showDialog`
getResultFromTable(String, ResultProducer, Object[]) - Method in class weka.experiment.DatabaseUtils
  Executes a database query to extract a result for the supplied key from the database.
getResultListener() - Method in class weka.experiment.Experiment
  Gets the result listener where results will be sent.
getResultNames() - Method in class weka.experiment.AveragingResultProducer
  Gets the names of each of the columns produced for a single run.
getResultNames() - Method in class weka.experiment.ClassifierSplitEvaluator
  Gets the names of each of the result columns produced for a single run.
getResultNames() - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator
  Gets the names of each of the result columns produced for a single run.
getResultNames() - Method in class weka.experiment.CrossValidationResultProducer
  Gets the names of each of the columns produced for a single run.
getResultNames() - Method in class weka.experiment.DatabaseResultProducer
  Gets the names of each of the columns produced for a single run.
getResultNames() - Method in class weka.experiment.LearningRateResultProducer
  Gets the names of each of the columns produced for a single run.
getResultNames() - Method in class weka.experiment.RandomSplitResultProducer
  Gets the names of each of the columns produced for a single run.
getResultNames() - Method in class weka.experiment.RegressionSplitEvaluator
  Gets the names of each of the result columns produced for a single run.
getResultNames() - Method in interface weka.experiment.ResultProducer
  Gets the names of each of the result columns produced for a single run.
getResultNames() - Method in interface weka.experiment.SplitEvaluator
  Gets the names of each of the result columns produced for a single run.
getResultProducer() - Method in class weka.experiment.AveragingResultProducer
  Get the ResultProducer.
getResultProducer() - Method in class weka.experiment.DatabaseResultProducer
  Get the ResultProducer.
getResultProducer() - Method in class weka.experiment.Experiment
  Get the result producer used for the current experiment.
getResultProducer() - Method in class weka.experiment.LearningRateResultProducer
  Get the ResultProducer.
getResultSet() - Method in class weka.experiment.DatabaseUtils
  Gets the results generated by a previous query.
getResultsetKeyColumns() - Method in class weka.experiment.PairedTTester
  Get the value of ResultsetKeyColumns.
getResultsetName(int) - Method in class weka.experiment.PairedTTester
  Gets a string descriptive of the specified resultset.
getResultsTableName(ResultProducer) - Method in class weka.experiment.DatabaseUtils
  Gets the name of the experiment table that stores results from a particular ResultProducer.
getResultTypes() - Method in class weka.experiment.AveragingResultProducer
  Gets the data types of each of the columns produced for a single run.
getResultTypes() - Method in class weka.experiment.ClassifierSplitEvaluator
  Gets the data types of each of the result columns produced for a single run.
getResultTypes() - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator
  Gets the data types of each of the result columns produced for a single run.
getResultTypes() - Method in class weka.experiment.CrossValidationResultProducer
  Gets the data types of each of the columns produced for a single run.
getResultTypes() - Method in class weka.experiment.DatabaseResultProducer
  Gets the data types of each of the columns produced for a single run.
getResultTypes() - Method in class weka.experiment.LearningRateResultProducer
  Gets the data types of each of the columns produced for a single run.
getResultTypes() - Method in class weka.experiment.RandomSplitResultProducer
  Gets the data types of each of the columns produced for a single run.
getResultTypes() - Method in class weka.experiment.RegressionSplitEvaluator
  Gets the data types of each of the result columns produced for a single run.
getResultTypes() - Method in interface weka.experiment.ResultProducer
  Gets the data types of each of the result columns produced for a single run.
getResultTypes() - Method in interface weka.experiment.SplitEvaluator
  Gets the data types of each of the result columns produced for a single run.
getReturnValue() - Method in class weka.gui.DatabaseConnectionDialog
  Returns which of OK or cancel was clicked from dialog
getRidge() - Method in class weka.classifiers.functions.LinearRegression
  Get the value of Ridge.
getRidge() - Method in class weka.classifiers.functions.Logistic
  Gets the ridge in the log-likelihood.
getRidge() - Method in class weka.classifiers.functions.RBFNetwork
  Gets the ridge value.
getRocAnalysis() - Method in class weka.associations.Tertius
  Get the value of rocAnalysis.
getROCArea(Instances) - Static method in class weka.classifiers.evaluation.ThresholdCurve
  Calculates the area under the ROC curve.
getROCString() - Method in class weka.gui.visualize.ThresholdVisualizePanel
  This extracts the ROC area string
getRoot() - Method in class weka.gui.treevisualizer.Node
  Get the value of root.
getRootNode() - Method in class weka.core.xml.XMLDocument
  returns the current root node
getRow(int) - Method in class weka.core.Matrix
  Deprecated. Gets a row of the matrix and returns it as double array.
getRow() - Static method in class weka.gui.experiment.ExperimenterDefaults
  the comma-separated list of attribute names that identify a row
getRowCount() - Method in class weka.gui.arffviewer.ArffTableModel
  returns the number of rows in the model
getRowCount() - Method in class weka.gui.TableMap
getRowDimension() - Method in class weka.classifiers.functions.pace.Matrix
  Get row dimension.
getRowDimension() - Method in class weka.core.matrix.Matrix
  Get row dimension.
getRowPackedCopy() - Method in class weka.classifiers.functions.pace.Matrix
  Make a one-dimensional row packed copy of the internal array.
getRowPackedCopy() - Method in class weka.core.matrix.Matrix
  Make a one-dimensional row packed copy of the internal array.
getRsource() - Method in class weka.gui.treevisualizer.Edge
  Get the value of rsource.
getRtarget() - Method in class weka.gui.treevisualizer.Edge
  Get the value of rtarget.
getRuleset() - Method in class weka.classifiers.rules.JRip
  Get the ruleset generated by Ripper
getRuleset() - Method in class weka.classifiers.rules.RuleStats
  Get the ruleset of the stats
getRulesetSize() - Method in class weka.classifiers.rules.RuleStats
  Get the size of the ruleset in the stats
getRuleStats(int) - Method in class weka.classifiers.rules.JRip
  Get the statistics of the ruleset in the given position
getRunColumn() - Method in class weka.experiment.PairedTTester
  Get the value of RunColumn.
getRunLower() - Method in class weka.experiment.Experiment
  Get the lower run number for the experiment.
getRuns() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
getRuns() - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber
getRuns() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
getRuns() - Method in class weka.classifiers.bayes.net.search.global.TabuSearch
getRuns() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
getRuns() - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber
getRuns() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
getRuns() - Method in class weka.classifiers.bayes.net.search.local.TabuSearch
getRunUpper() - Method in class weka.experiment.Experiment
  Get the upper run number for the experiment.
getS() - Method in class weka.core.matrix.SingularValueDecomposition
  Return the diagonal matrix of singular values
getSampleSize() - Method in class weka.attributeSelection.ReliefFAttributeEval
  Get the number of instances used for estimating attributes
getSampleSize() - Method in class weka.classifiers.functions.LeastMedSq
  gets number of samples
getSampleSizePercent() - Method in class weka.filters.supervised.instance.Resample
  Gets the subsample size as a percentage of the original set.
getSampleSizePercent() - Method in class weka.filters.unsupervised.instance.Resample
  Gets the subsample size as a percentage of the original set.
getSaveDialogTitle() - Method in class weka.gui.visualize.PrintableComponent
  returns the title for the save dialog
getSaveDialogTitle() - Method in interface weka.gui.visualize.PrintableHandler
  returns the title for the save dialog
getSaveDialogTitle() - Method in class weka.gui.visualize.PrintablePanel
  returns the title for the save dialog
getSaveInstanceData() - Method in class weka.classifiers.trees.ADTree
  Gets whether the tree is to save instance data.
getSaveInstanceData() - Method in class weka.classifiers.trees.J48
  Check whether instance data is to be saved.
getSaveInstanceData() - Method in class weka.clusterers.Cobweb
  Get the value of saveInstances.
getSaveInstances() - Method in class weka.classifiers.trees.M5P
  Get whether instance data is being save.
getSaver() - Method in class weka.gui.beans.Saver
  Get the saver
getScalingEnabled() - Method in class weka.gui.visualize.JComponentWriter
  whether scaling is enabled or ignored
getScoreType() - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
  get quality measure to be used in searching for networks.
getSearch() - Method in class weka.classifiers.meta.AttributeSelectedClassifier
  Gets the search method used
getSearch() - Method in class weka.filters.supervised.attribute.AttributeSelection
  Get the name of the search method
getSearchAlgorithm() - Method in class weka.classifiers.bayes.BayesNet
  Get the SearchAlgorithm used as the search algorithm
getSearchBackwards() - Method in class weka.attributeSelection.GreedyStepwise
  Get whether to search backwards
getSearchPath() - Method in class weka.classifiers.trees.ADTree
  Gets the method of searching the tree for a new insertion.
getSearchPercent() - Method in class weka.attributeSelection.RandomSearch
  get the percentage of the search space to consider
getSearchString() - Method in class weka.gui.arffviewer.ArffTable
  returns the search string, can be NULL if no search string is set
getSearchTermination() - Method in class weka.attributeSelection.BestFirst
  Get the termination criterion (number of non-improving nodes).
getSecondValueIndex() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues
  Get the index of the second value used.
getSecondValueIndex() - Method in class weka.filters.unsupervised.attribute.SwapValues
  Get the index of the second value used.
getSeed() - Method in class weka.attributeSelection.GeneticSearch
  get the value of the random number generator's seed
getSeed() - Method in class weka.attributeSelection.OneRAttributeEval
  Get the random number seed
getSeed() - Method in class weka.attributeSelection.ReliefFAttributeEval
  Get the seed used for randomly sampling instances.
getSeed() - Method in class weka.attributeSelection.WrapperSubsetEval
  Get the random number seed used for cross validation
getSeed() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
getSeed() - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber
getSeed() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
getSeed() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
getSeed() - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber
getSeed() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
getSeed() - Method in class weka.classifiers.BVDecompose
  Gets the random number seed
getSeed() - Method in class weka.classifiers.BVDecomposeSegCVSub
  Gets the random number seed
getSeed() - Method in class weka.classifiers.evaluation.EvaluationUtils
  Gets the seed for randomization during cross-validation
getSeed() - Method in class weka.classifiers.functions.MultilayerPerceptron
getSeed() - Method in class weka.classifiers.functions.VotedPerceptron
  Get the value of Seed.
getSeed() - Method in class weka.classifiers.functions.Winnow
  Get the value of Seed.
getSeed() - Method in class weka.classifiers.meta.MultiScheme
  Gets the random number seed.
getSeed() - Method in class weka.classifiers.RandomizableClassifier
  Gets the seed for the random number generations
getSeed() - Method in class weka.classifiers.RandomizableIteratedSingleClassifierEnhancer
  Gets the seed for the random number generations
getSeed() - Method in class weka.classifiers.RandomizableMultipleClassifiersCombiner
  Gets the seed for the random number generations
getSeed() - Method in class weka.classifiers.RandomizableSingleClassifierEnhancer
  Gets the seed for the random number generations
getSeed() - Method in class weka.classifiers.rules.ConjunctiveRule
getSeed() - Method in class weka.classifiers.rules.JRip
getSeed() - Method in class weka.classifiers.rules.PART
  Get the value of Seed.
getSeed() - Method in class weka.classifiers.rules.Ridor
getSeed() - Method in class weka.classifiers.trees.J48
  Get the value of Seed.
getSeed() - Method in class weka.classifiers.trees.RandomForest
  Gets the seed for the random number generations
getSeed() - Method in class weka.classifiers.trees.RandomTree
  Gets the seed for the random number generations
getSeed() - Method in class weka.classifiers.trees.REPTree
  Get the value of Seed.
getSeed() - Method in class weka.clusterers.EM
  Get the random number seed
getSeed() - Method in class weka.clusterers.FarthestFirst
  Get the random number seed
getSeed() - Method in class weka.clusterers.SimpleKMeans
  Get the random number seed
getSeed() - Method in interface weka.core.Randomizable
  Gets the seed for the random number generations
getSeed() - Method in class weka.datagenerators.BIRCHCluster
  Gets the random number seed.
getSeed() - Method in class weka.datagenerators.RDG1
  Gets the random number seed.
getSeed() - Method in class weka.filters.supervised.attribute.ClassOrder
  Get the current randomization seed
getSeed() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds
  Gets the random number seed used for shuffling the dataset.
getSeed() - Method in class weka.filters.unsupervised.instance.RemoveFolds
  Gets the random number seed used for shuffling the dataset.
getSeed() - Method in class weka.gui.beans.CrossValidationFoldMaker
  Get the currently set seed
getSeed() - Method in class weka.gui.beans.TrainTestSplitMaker
  Get the value of the random seed
getSelectedAttributes() - Method in class weka.gui.AttributeSelectionPanel
  Gets an array containing the indices of all selected attributes.
getSelectedBuffer() - Method in class weka.gui.ResultHistoryPanel
  Gets the buffer associated with the currently selected item in the list.
getSelectedName() - Method in class weka.gui.ResultHistoryPanel
  Get the name of the currently selected item in the list
getSelectedObject() - Method in class weka.gui.ResultHistoryPanel
  Gets the object associated with the currently selected item in the list.
getSelectedRange() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Get the value of m_SelectedRange.
getSelectedTag() - Method in class weka.core.SelectedTag
  Gets the selected Tag.
getSelection() - Method in class weka.core.Range
  Gets an array containing all the selected values, in the order that they were selected (or ascending order if range inversion is on)
getSelectionModel() - Method in class weka.gui.AttributeListPanel
  Gets the selection model used by the table.
getSelectionModel() - Method in class weka.gui.AttributeSelectionPanel
  Gets the selection model used by the table.
getSelectionModel() - Method in class weka.gui.ResultHistoryPanel
  Gets the selection model used by the results list.
getSelectionThreshold() - Method in class weka.attributeSelection.RaceSearch
  Returns the threshold so that the AttributeSelection module can discard attributes from the ranking.
getSeparatingThreshold() - Method in class weka.classifiers.functions.pace.ChisqMixture
  Gets the separating threshold value.
getSeparatingThreshold() - Method in class weka.classifiers.functions.pace.NormalMixture
  Gets the separating threshold value.
getSeperator() - Method in class weka.gui.HierarchyPropertyParser
  Get the seperator between levels.
getSequentialAttIndex(int) - Method in class weka.classifiers.lazy.LBR.Indexes
  Returns the boolean value at the specified index in the Sequential Attribute Indexes array
getSequentialInstanceIndex(int) - Method in class weka.classifiers.lazy.LBR.Indexes
  Returns the boolean value at the specified index in the Sequential Instance Indexes array
getSequentialNumAttributes() - Method in class weka.classifiers.lazy.LBR.Indexes
  Returns the number of attributes in the Sequential array
getSequentialNumInstances() - Method in class weka.classifiers.lazy.LBR.Indexes
  Returns the number of instances in the Sequential array
getSetNumber() - Method in class weka.gui.beans.BatchClassifierEvent
  Get the set number (ie which fold this is)
getSetNumber() - Method in class weka.gui.beans.BatchClustererEvent
  Get the set number (ie which fold this is)
getSetNumber() - Method in class weka.gui.beans.TestSetEvent
  Get the test set number (eg.
getSetNumber() - Method in class weka.gui.beans.TrainingSetEvent
  Get the set number (eg.
getShape() - Method in class weka.gui.treevisualizer.Node
  Get the value of shape.
getShowStdDevs() - Method in class weka.experiment.PairedTTester
  Returns true if standard deviations have been requested.
getShowStdDevs() - Static method in class weka.gui.experiment.ExperimenterDefaults
  returns whether StdDevs are shown by default
getShrinkage() - Method in class weka.classifiers.meta.AdditiveRegression
  Get the shrinkage rate.
getShrinkage() - Method in class weka.classifiers.meta.LogitBoost
  Get the value of Shrinkage.
getShuffle() - Method in class weka.classifiers.rules.Ridor
getSigma() - Method in class weka.attributeSelection.ReliefFAttributeEval
  Get the value of sigma.
getSigma() - Method in class weka.classifiers.BVDecompose
  Get the calculated sigma squared
getSignificance() - Static method in class weka.gui.experiment.ExperimenterDefaults
  returns the default significance
getSignificanceLevel() - Method in class weka.associations.Apriori
  Get the value of significanceLevel.
getSignificanceLevel() - Method in class weka.attributeSelection.RaceSearch
  Get the significance level
getSignificanceLevel() - Method in class weka.experiment.PairedTTester
  Get the value of SignificanceLevel.
getSilent() - Method in class weka.classifiers.CheckClassifier
  Get whether silent mode is turned on
getSimpleStats(int) - Method in class weka.classifiers.rules.RuleStats
  Get the simple stats of one rule, including 6 parameters: 0: coverage; 1:uncoverage; 2: true positive; 3: true negatives; 4: false positives; 5: false negatives
getSIndex() - Method in class weka.gui.visualize.VisualizePanel
  Get the index of the shape selected for creating splits.
getSineFlag() - Method in class weka.datagenerators.BIRCHCluster
  Gets the sine flag (option S).
getSingleIndex() - Method in class weka.core.SingleIndex
  Gets the string representing the selected range of values
getSingleModeFlag() - Method in class weka.datagenerators.BIRCHCluster
  Gets the single mode flag.
getSingleModeFlag() - Method in class weka.datagenerators.RDG1
  Gets the single mode flag.
getSingleton() - Static method in class weka.gui.beans.KnowledgeFlowApp
  Return the singleton instance of the KnowledgeFlow
getSingularValues() - Method in class weka.core.matrix.SingularValueDecomposition
  Return the one-dimensional array of singular values
getSlope() - Method in class weka.classifiers.functions.SimpleLinearRegression
  Returns the slope of the function.
getSmoothing() - Method in class weka.classifiers.trees.m5.Rule
  Get whether or not smoothing has been turned on
getSmoothingParameter() - Method in class weka.classifiers.bayes.ComplementNaiveBayes
  Gets the smoothing value to be used to avoid zero WordGivenClass probabilities.
getSource() - Method in class weka.gui.beans.BeanConnection
  returns the source BeanInstance for this connection
getSource() - Method in class weka.gui.treevisualizer.Edge
  Get the value of source.
getSparseData() - Method in class weka.experiment.InstanceQuery
  Gets whether data is to be returned as a set of sparse instances
getSplitByDataSet() - Method in class weka.experiment.RemoteExperiment
  Returns true if sub experiments are to be created on the basis of data set..
getSplitEvaluator() - Method in class weka.experiment.CrossValidationResultProducer
  Get the SplitEvaluator.
getSplitEvaluator() - Method in class weka.experiment.RandomSplitResultProducer
  Get the SplitEvaluator.
getSplitOnResiduals() - Method in class weka.classifiers.trees.LMT
  Get the value of splitOnResiduals.
getSplitPoint() - Method in class weka.filters.unsupervised.instance.RemoveWithValues
  Get the split point used for numeric selection
getSquaredError() - Method in class weka.clusterers.SimpleKMeans
getStartSet() - Method in class weka.attributeSelection.BestFirst
  Returns a list of attributes (and or attribute ranges) as a String
getStartSet() - Method in class weka.attributeSelection.GeneticSearch
  Returns a list of attributes (and or attribute ranges) as a String
getStartSet() - Method in class weka.attributeSelection.GreedyStepwise
  Returns a list of attributes (and or attribute ranges) as a String
getStartSet() - Method in class weka.attributeSelection.RandomSearch
  Returns a list of attributes (and or attribute ranges) as a String
getStartSet() - Method in class weka.attributeSelection.Ranker
  Returns a list of attributes (and or attribute ranges) as a String
getStartSet() - Method in interface weka.attributeSelection.StartSetHandler
  Returns a list of attributes (and or attribute ranges) as a String
getStaticIcon() - Method in class weka.gui.beans.BeanVisual
  Returns the static icon
getStatus() - Method in class weka.gui.beans.IncrementalClassifierEvent
  Get the status
getStatus() - Method in class weka.gui.beans.InstanceEvent
  Get the status
getStatusMessage() - Method in class weka.experiment.TaskStatusInfo
  Get the status message.
getStdDevPrec() - Method in class weka.experiment.PairedTTester
  Gets the precision used for printing the std.
getStdDevPrec() - Method in class weka.gui.experiment.OutputFormatDialog
  Gets the precision used for printing the std.
getStdDevPrecision() - Static method in class weka.gui.experiment.ExperimenterDefaults
  returns the default precision for the stddevs
getStepSize() - Method in class weka.experiment.LearningRateResultProducer
  Get the value of StepSize.
getStringSelection() - Method in class weka.gui.arffviewer.ArffTable
  returns the selected content in a StringSelection that can be copied to the clipboard and used in Excel, if nothing is selected the whole table is copied to the clipboard
getStroke() - Method in class weka.gui.visualize.PostscriptGraphics
getStructure() - Method in class weka.core.converters.AbstractLoader
getStructure() - Method in class weka.core.converters.ArffLoader
  Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
getStructure() - Method in class weka.core.converters.C45Loader
  Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
getStructure() - Method in class weka.core.converters.CSVLoader
  Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
getStructure() - Method in class weka.core.converters.DatabaseLoader
  Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
getStructure() - Method in interface weka.core.converters.Loader
  Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
getStructure() - Method in class weka.core.converters.SerializedInstancesLoader
  Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
getStructure() - Method in class weka.gui.beans.IncrementalClassifierEvent
  Get the instances structure (may be null if this is not a NEW_BATCH event)
getStructure() - Method in class weka.gui.beans.InstanceEvent
  Get the instances structure (may be null if this is not a FORMAT_AVAILABLE event)
getSubFlow() - Method in class weka.gui.beans.MetaBean
getSubtreeRaising() - Method in class weka.classifiers.trees.J48
  Get the value of subtreeRaising.
getSuitableTargets(EventSetDescriptor) - Method in class weka.gui.beans.MetaBean
  Return a list of input beans capable of receiving the supplied event
getSummary() - Method in class weka.gui.SetInstancesPanel
  Gets the instances summary panel associated with this panel
getSumOfCounts() - Method in class weka.estimators.DiscreteEstimator
  Get the sum of all the counts
getSystemInfo() - Method in class weka.core.SystemInfo
  returns a copy of the system info.
getSystemLookAndFeel() - Static method in class weka.gui.LookAndFeel
  returns the system LnF classname
getTabbedPane() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  returns the tabbedpane instance
getTable() - Method in class weka.gui.arffviewer.ArffPanel
  returns the table component
getTableCellRendererComponent(JTable, Object, boolean, boolean, int, int) - Method in class weka.gui.arffviewer.ArffTableCellRenderer
  Returns the default table cell renderer.
getTableName() - Method in class weka.core.converters.DatabaseSaver
  Gets the table's name
getTabuList() - Method in class weka.classifiers.bayes.net.search.global.TabuSearch
getTabuList() - Method in class weka.classifiers.bayes.net.search.local.TabuSearch
getTags() - Method in class weka.core.SelectedTag
  Gets the set of all valid Tags.
getTags() - Method in class weka.gui.CostMatrixEditor
  Some objects can return tags, but a cost matrix cannot.
getTags() - Method in class weka.gui.GenericArrayEditor
  Returns null as we don't support getting values as tags.
getTags() - Method in class weka.gui.GenericObjectEditor
  Returns null as we don't support getting values as tags.
getTags() - Method in class weka.gui.SelectedTagEditor
  Gets the list of tags that can be selected from.
getTags() - Method in class weka.gui.SimpleDateFormatEditor
  Some objects can return tags, but a date format cannot.
getTarget() - Method in class weka.gui.beans.BeanConnection
  Returns the target BeanInstance for this connection
getTarget() - Method in class weka.gui.treevisualizer.Edge
  Get the value of target.
getTaskResult() - Method in class weka.experiment.TaskStatusInfo
  Get the returnable result of this task.
getTaskStatus() - Method in class weka.experiment.RemoteExperimentSubTask
getTaskStatus() - Method in interface weka.experiment.Task
  Clients should be able to call this method at any time to obtain information on a current task.
getTaskStatus() - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
  Return status information for this sub task
getTestOrTrain() - Method in class weka.gui.beans.BatchClustererEvent
  Get whether the set of instances is a test or a training set
getTestPredictions(Classifier, Instances) - Method in class weka.classifiers.evaluation.EvaluationUtils
  Generate a bunch of predictions ready for processing, by performing a evaluation on a test set assuming the classifier is already trained.
getTestSet() - Method in class weka.gui.beans.BatchClassifierEvent
  Get the test set
getTestSet() - Method in class weka.gui.beans.BatchClustererEvent
  Get the training/test set
getTestSet() - Method in class weka.gui.beans.TestSetEvent
  Get the test set instances
getText() - Method in class weka.gui.beans.BeanVisual
  Get the visual's label
getText() - Method in class weka.gui.beans.TextEvent
  Describe `getText` method here.
getTextTitle() - Method in class weka.gui.beans.TextEvent
  Describe `getTextTitle` method here.
getTFTransform() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Gets whether if the word frequencies should be transformed into log(1+fij) where fij is the frequency of word i in document(instance) j.
getThreshold() - Method in class weka.attributeSelection.GreedyStepwise
  Returns the threshold so that the AttributeSelection module can discard attributes from the ranking.
getThreshold() - Method in class weka.attributeSelection.RaceSearch
  Get the threshold
getThreshold() - Method in interface weka.attributeSelection.RankedOutputSearch
  Gets the threshold by which attributes can be discarded.
getThreshold() - Method in class weka.attributeSelection.Ranker
  Returns the threshold so that the AttributeSelection module can discard attributes from the ranking.
getThreshold() - Method in class weka.attributeSelection.WrapperSubsetEval
  Get the value of the threshold
getThreshold() - Method in class weka.classifiers.functions.PaceRegression
  Gets the threshold for olsc estimator
getThreshold() - Method in class weka.classifiers.functions.Winnow
  Get the value of Threshold.
getThreshold() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified
  Gets the threshold for the max error when predicting a numeric class.
getThresholdInstance(Instances, double) - Static method in class weka.classifiers.evaluation.ThresholdCurve
  Gets the index of the instance with the closest threshold value to the desired target
getTimestamp() - Static method in class weka.experiment.CrossValidationResultProducer
  Gets a Double representing the current date and time.
getTimestamp() - Static method in class weka.experiment.RandomSplitResultProducer
  Gets a Double representing the current date and time.
getTitle() - Method in class weka.gui.arffviewer.ArffPanel
  returns the title for the Tab, i.e.
getToken(StreamTokenizer) - Static method in class weka.core.converters.ConverterUtils
  Gets token.
getToleranceParameter() - Method in class weka.attributeSelection.SVMAttributeEval
  Get the value of T used with SMO
getToleranceParameter() - Method in class weka.classifiers.functions.SMO
  Get the value of tolerance parameter.
getToleranceParameter() - Method in class weka.classifiers.functions.SMOreg
  Get the value of tolerance parameter.
getToolTipText(MouseEvent) - Method in class weka.gui.AttributeVisualizationPanel
  Returns "<nominal value> [<nominal value count>]" if displaying a bar plot and mouse is on some bar.
getToolTipText(PrintableComponent) - Static method in class weka.gui.visualize.PrintableComponent
  Returns a tooltip only if the user wants it.
getTop() - Method in class weka.gui.treevisualizer.Node
  Get the value of top.
getTotalCount(Node, int) - Static method in class weka.gui.treevisualizer.Node
  Recursively finds the total number of nodes there are.
getTotalGCount(Node, int) - Static method in class weka.gui.treevisualizer.Node
  Recursively finds the total number of groups of siblings there are.
getTotalHeight(Node, int) - Static method in class weka.gui.treevisualizer.Node
  Recursively finds the total number of levels there are.
getTPRate() - Method in class weka.associations.tertius.Rule
  Get the rate of True Positive instances of this rule.
getTrainingSet() - Method in class weka.gui.beans.TrainingSetEvent
  Get the training instances
getTrainingTime() - Method in class weka.classifiers.functions.MultilayerPerceptron
getTrainIterations() - Method in class weka.classifiers.BVDecompose
  Gets the maximum number of boost iterations
getTrainPercent() - Method in class weka.experiment.RandomSplitResultProducer
  Get the value of TrainPercent.
getTrainPercent() - Method in class weka.gui.beans.TrainTestSplitMaker
  Get the percentage of the data that will be in the training portion of the split
getTrainPercentage() - Static method in class weka.gui.experiment.ExperimenterDefaults
  returns the training percentage in case of splits
getTrainPoolSize() - Method in class weka.classifiers.BVDecompose
  Get the number of instances in the training pool.
getTrainSet() - Method in class weka.gui.beans.BatchClassifierEvent
  Get the train set
getTrainSize() - Method in class weka.classifiers.BVDecomposeSegCVSub
  Get the training size
getTrainTestPredictions(Classifier, Instances, Instances) - Method in class weka.classifiers.evaluation.EvaluationUtils
  Generate a bunch of predictions ready for processing, by performing a evaluation on a test set after training on the given training set.
getTransform() - Method in class weka.gui.visualize.PostscriptGraphics
getTransformAllValues() - Method in class weka.filters.supervised.attribute.NominalToBinary
  Gets if all nominal values are turned into new attributes, not only if there are more than 2.
getTransformBackToOriginal() - Method in class weka.attributeSelection.PrincipalComponents
  Gets whether the data is to be transformed back to the original space.
getTrimingThreshold() - Method in class weka.classifiers.functions.pace.ChisqMixture
  Gets the triming thresholding value.
getTrimingThreshold() - Method in class weka.classifiers.functions.pace.NormalMixture
  Gets the triming thresholding value.
getTrueNegative() - Method in class weka.classifiers.evaluation.TwoClassStats
  Gets the number of negative instances predicted as negative
getTruePositive() - Method in class weka.classifiers.evaluation.TwoClassStats
  Gets the number of positive instances predicted as positive
getTruePositiveRate() - Method in class weka.classifiers.evaluation.TwoClassStats
  Calculate the true positive rate.
getTStart() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
getTStart() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
getTwoClassStats(int) - Method in class weka.classifiers.evaluation.ConfusionMatrix
  Gets the performance with respect to one of the classes as a TwoClassStats object.
getType() - Method in class weka.associations.tertius.IndividualLiteral
getType() - Method in class weka.associations.tertius.LiteralSet
  Give the type of properties in this set (individual or part properties).
getType() - Method in class weka.classifiers.functions.neural.NeuralConnection
getType(int) - Method in class weka.gui.arffviewer.ArffTableModel
  returns the TYPE of the attribute at the given position
getType(int, int) - Method in class weka.gui.arffviewer.ArffTableModel
  returns the TYPE of the attribute at the given position
getType(int) - Method in class weka.gui.arffviewer.ArffTableSorter
  returns the TYPE of the attribute at the given position
getType(int, int) - Method in class weka.gui.arffviewer.ArffTableSorter
  returns the TYPE of the attribute at the given position
getU() - Method in class weka.core.Matrix
  Deprecated. Returns the U part of the matrix.
getU() - Method in class weka.core.matrix.LUDecomposition
  Return upper triangular factor
getU() - Method in class weka.core.matrix.SingularValueDecomposition
  Return the left singular vectors
getUnpruned() - Method in class weka.classifiers.rules.PART
  Get the value of unpruned.
getUnpruned() - Method in class weka.classifiers.trees.J48
  Get the value of unpruned.
getUnpruned() - Method in class weka.classifiers.trees.m5.M5Base
  Get whether unpruned tree/rules are being generated
getUnpruned() - Method in class weka.classifiers.trees.m5.Rule
  Get whether unpruned tree/rules are being generated
getUpdateCount() - Method in class weka.core.converters.DatabaseConnection
  Dewtermines if the current query retrieves a result set or updates a table
getUpdateIncrementalClassifier() - Method in class weka.gui.beans.Classifier
getUpper() - Method in class weka.gui.experiment.RunNumberPanel
  Gets the current upper run number.
getUpperBoundMinSupport() - Method in class weka.associations.Apriori
  Get the value of upperBoundMinSupport.
getUpperCase() - Method in class weka.core.converters.DatabaseConnection
  Check if the property checkUpperCaseNames in the DatabaseUtils file is set to true or false.
getUpperNumericBound() - Method in class weka.core.Attribute
  Returns the upper bound of a numeric attribute.
getUpperSize() - Method in class weka.experiment.LearningRateResultProducer
  Get the value of UpperSize.
getUrl() - Method in interface weka.core.converters.DatabaseConverter
getUrl() - Method in class weka.core.converters.DatabaseLoader
  Gets the URL
getUrl() - Method in class weka.core.converters.DatabaseSaver
  Gets the database URL
getURL() - Method in class weka.gui.DatabaseConnectionDialog
  Returns URL from dialog
getURL(String, String) - Static method in class weka.gui.Loader
  returns a URL for the given filename, can be NULL if it fails
getURL(String) - Method in class weka.gui.Loader
  returns a URL for the given filename, can be NULL if it fails
getUseADTree() - Method in class weka.classifiers.bayes.BayesNet
  Method declaration
getUseArcReversal() - Method in class weka.classifiers.bayes.net.search.global.HillClimber
  get use the arc reversal operation
getUseArcReversal() - Method in class weka.classifiers.bayes.net.search.local.HillClimber
  get use the arc reversal operation
getUseBetterEncoding() - Method in class weka.filters.supervised.attribute.Discretize
  Gets whether better encoding is to be used for MDL.
getUseClassification() - Static method in class weka.gui.experiment.ExperimenterDefaults
  whether classification or regression is used
getUseCrossOver() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
getUseCrossOver() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
getUseCrossValidation() - Method in class weka.classifiers.functions.SimpleLogistic
  Get the value of useCrossValidation.
getUsedAttributes() - Method in class weka.classifiers.trees.lmt.LogisticBase
  Returns an array of the indices of the attributes used in the logistic model.
getUseEqualFrequency() - Method in class weka.filters.unsupervised.attribute.Discretize
  Get the value of UseEqualFrequency.
getUseEqualFrequency() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize
  Get the value of UseEqualFrequency.
getUseGUI() - Method in class weka.core.Memory
  whether to display a dialog in case of a problem (= TRUE) or just print on stderr (= FALSE)
getUseIBk() - Method in class weka.classifiers.rules.DecisionTable
  Gets whether IBk is being used instead of the majority class
getUseKernelEstimator() - Method in class weka.classifiers.bayes.NaiveBayes
  Gets if kernel estimator is being used.
getUseKononenko() - Method in class weka.filters.supervised.attribute.Discretize
  Gets whether Kononenko's MDL criterion is to be used.
getUseLaplace() - Method in class weka.classifiers.trees.J48
  Get the value of useLaplace.
getUseMissing() - Method in class weka.filters.unsupervised.attribute.AddNoise
  Gets the flag if missing values are treated as extra values.
getUseMutation() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
getUseMutation() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
getUseProb() - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
getUsePropertyIterator() - Method in class weka.experiment.Experiment
  Gets whether the custom property iterator should be used.
getUsePruning() - Method in class weka.classifiers.rules.JRip
getUser() - Method in interface weka.core.converters.DatabaseConverter
getUser() - Method in class weka.core.converters.DatabaseLoader
  Gets the user name
getUser() - Method in class weka.core.converters.DatabaseSaver
  Gets the database user
getUseRBF() - Method in class weka.classifiers.functions.SMO
  Check if the RBF kernel is to be used.
getUseRBF() - Method in class weka.classifiers.functions.SMOreg
  Check if the RBF kernel is to be used.
getUseRelativePaths() - Static method in class weka.gui.experiment.ExperimenterDefaults
  whether relative paths are used by default
getUseResampling() - Method in class weka.classifiers.meta.AdaBoostM1
  Get whether resampling is turned on
getUseResampling() - Method in class weka.classifiers.meta.LogitBoost
  Get whether resampling is turned on
getUseResampling() - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost
  Get whether resampling is turned on
getUsername() - Method in class weka.experiment.DatabaseUtils
  Get the database username
getUsername() - Method in class weka.gui.DatabaseConnectionDialog
  Returns Username from dialog
getUseStoplist() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Gets whether if the words on the stoplist are to be ignored (The stoplist is in weka.core.StopWords).
getUseSupervisedDiscretization() - Method in class weka.classifiers.bayes.NaiveBayes
  Get whether supervised discretization is to be used.
getUseTournamentSelection() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
getUseTournamentSelection() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
getUseTraining() - Method in class weka.attributeSelection.ClassifierSubsetEval
  Get if training data is to be used instead of hold out/test data
getUseTree() - Method in class weka.classifiers.trees.m5.Rule
  get whether an m5 tree is being used rather than rules
getUseUnsmoothed() - Method in class weka.classifiers.trees.m5.M5Base
  Get whether or not smoothing is being used
getV() - Method in class weka.core.matrix.EigenvalueDecomposition
  Return the eigenvector matrix
getV() - Method in class weka.core.matrix.SingularValueDecomposition
  Return the right singular vectors
getValidating() - Method in class weka.core.xml.XMLDocument
  returns whether a validating parser is used
getValidating() - Method in class weka.core.xml.XMLOptions
  returns whether a validating parser is used
getValidationChunkSize() - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost
  Get the validation chunk size
getValidationSetSize() - Method in class weka.classifiers.functions.MultilayerPerceptron
getValidationThreshold() - Method in class weka.classifiers.functions.MultilayerPerceptron
getValue() - Method in class weka.classifiers.trees.adtree.PredictionNode
  Gets the prediction value of the node.
getValue() - Method in class weka.gui.CostMatrixEditor
  Gets the cost matrix that is being edited.
getValue() - Method in class weka.gui.GenericArrayEditor
  Gets the current object array.
getValue() - Method in class weka.gui.GenericObjectEditor
  Gets the current Object.
getValue() - Method in class weka.gui.HierarchyPropertyParser
  Get the value of current node
getValue() - Method in class weka.gui.SimpleDateFormatEditor
  Gets the date format that is being edited.
getValueAt(int, int) - Method in class weka.gui.arffviewer.ArffTableModel
  returns the value for the cell at columnindex and rowIndex
getValueAt(int, int) - Method in class weka.gui.TableMap
getValueAt(int, int) - Method in class weka.gui.TableSorter
getValueIndices() - Method in class weka.filters.unsupervised.attribute.MakeIndicator
  Get the indices of the indicator values.
getValueRange() - Method in class weka.filters.unsupervised.attribute.MakeIndicator
  Get the range containing the indicator values.
getValues() - Method in class weka.gui.visualize.VisualizePanelEvent
getValuesOutput() - Method in class weka.associations.Tertius
  Get the value of valuesOutput.
getVarbValues() - Method in class weka.core.Optimization
  Get the variable values.
getVariance() - Method in class weka.classifiers.BVDecompose
  Get the calculated variance
getVarianceCovered() - Method in class weka.attributeSelection.PrincipalComponents
  Gets the proportion of total variance to account for when retaining principal components
getVerbose() - Method in class weka.associations.Apriori
  Gets whether algorithm is run in verbose mode
getVerbose() - Method in class weka.attributeSelection.ExhaustiveSearch
  get whether or not output is verbose
getVerbose() - Method in class weka.attributeSelection.RandomSearch
  get whether or not output is verbose
getVersion() - Method in class weka.core.xml.XMLSerialization
  returns the WEKA version with which the serialized object was created
getVisible() - Method in class weka.gui.treevisualizer.Node
  Get the value of visible.
getVisual() - Method in class weka.gui.beans.AbstractDataSink
  Get the visual being used by this data source.
getVisual() - Method in class weka.gui.beans.AbstractDataSource
  Get the visual being used by this data source.
getVisual() - Method in class weka.gui.beans.AbstractEvaluator
  Get the visual
getVisual() - Method in class weka.gui.beans.AbstractTestSetProducer
  Get the visual for this bean
getVisual() - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer
  Get the visual for this bean
getVisual() - Method in class weka.gui.beans.AbstractTrainingSetProducer
  Get the visual for this bean
getVisual() - Method in class weka.gui.beans.ClassAssigner
getVisual() - Method in class weka.gui.beans.Classifier
  Gets the visual appearance of this wrapper bean
getVisual() - Method in class weka.gui.beans.ClassValuePicker
getVisual() - Method in class weka.gui.beans.Clusterer
  Gets the visual appearance of this wrapper bean
getVisual() - Method in class weka.gui.beans.DataVisualizer
  Return the visual appearance of this bean
getVisual() - Method in class weka.gui.beans.Filter
  Get the visual appearance of this bean
getVisual() - Method in class weka.gui.beans.GraphViewer
  Get the visual appearance of this bean
getVisual() - Method in class weka.gui.beans.MetaBean
  Gets the visual appearance of this wrapper bean
getVisual() - Method in class weka.gui.beans.ModelPerformanceChart
  Return the visual appearance of this bean
getVisual() - Method in class weka.gui.beans.PredictionAppender
  Get the visual being used by this data source.
getVisual() - Method in class weka.gui.beans.StripChart
  Get the visual appearance of this bean
getVisual() - Method in class weka.gui.beans.TextViewer
  Get the visual appearance of this bean
getVisual() - Method in interface weka.gui.beans.Visible
  Get the visual representation
getVoteFlag() - Method in class weka.datagenerators.RDG1
  Gets the vote flag.
getWBias() - Method in class weka.classifiers.BVDecomposeSegCVSub
  Get the calculated bias according to the Webb definition
getWeightByConfidence() - Method in class weka.classifiers.misc.VFI
  Get whether feature intervals are being weighted by confidence
getWeightByDistance() - Method in class weka.attributeSelection.ReliefFAttributeEval
  Get whether nearest neighbours are being weighted by distance
getWeightingKernel() - Method in class weka.classifiers.lazy.LWL
  Gets the kernel weighting method to use.
getWeights() - Method in class weka.classifiers.functions.neural.NeuralNode
  call this function to get the weights array.
getWeights() - Method in interface weka.gui.boundaryvisualizer.DataGenerator
  Get weights
getWeights() - Method in class weka.gui.boundaryvisualizer.KDDataGenerator
getWeightThreshold() - Method in class weka.classifiers.meta.AdaBoostM1
  Get the degree of weight thresholding
getWeightThreshold() - Method in class weka.classifiers.meta.LogitBoost
  Get the degree of weight thresholding
getWholeDataErr() - Method in class weka.classifiers.rules.Ridor
getWidth() - Method in class weka.gui.beans.BeanInstance
  Gets the width of this bean
getWindowSize() - Method in class weka.classifiers.lazy.IBk
  Gets the maximum number of instances allowed in the training pool.
getWordsToKeep() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Gets the number of words (per class if there is a class attribute assigned) to attempt to keep.
getWrappedAlgorithm() - Method in class weka.gui.beans.Classifier
  Returns the wrapped classifier
getWrappedAlgorithm() - Method in class weka.gui.beans.Clusterer
  Returns the wrapped clusterer
getWrappedAlgorithm() - Method in class weka.gui.beans.Filter
  Get the filter wrapped by this bean
getWrappedAlgorithm() - Method in class weka.gui.beans.Loader
  Get the loader
getWrappedAlgorithm() - Method in class weka.gui.beans.Saver
  Get the saver
getWrappedAlgorithm() - Method in interface weka.gui.beans.WekaWrapper
  Get the algorithm
getWriteMode() - Method in class weka.core.converters.AbstractSaver
  Gets the write mode.
getWriteMode() - Method in interface weka.core.converters.Saver
  Gets the write mode
getWriter() - Method in class weka.core.converters.AbstractFileSaver
  Gets the writer
getWriter(String) - Method in class weka.gui.visualize.PrintableComponent
  returns the JComponentWriter associated with the given name, is `null` if not found
getWriter(String) - Method in interface weka.gui.visualize.PrintableHandler
  returns the JComponentWriter associated with the given name, is `null` if not found
getWriter(String) - Method in class weka.gui.visualize.PrintablePanel
  returns the JComponentWriter associated with the given name, is `null` if not found
getWriters() - Method in class weka.gui.visualize.PrintableComponent
  returns a Hashtable with the current available JComponentWriters in the save dialog.
getWriters() - Method in interface weka.gui.visualize.PrintableHandler
  returns a Hashtable with the current available JComponentWriters in the save dialog.
getWriters() - Method in class weka.gui.visualize.PrintablePanel
  returns a Hashtable with the current available JComponentWriters in the save dialog.
getWVariance() - Method in class weka.classifiers.BVDecomposeSegCVSub
  Get the calculated variance according to the Webb definition
getX() - Method in class weka.classifiers.functions.neural.NeuralConnection
getX() - Method in class weka.gui.beans.BeanInstance
  Gets the x coordinate of this bean
getXindex() - Method in class weka.gui.visualize.PlotData2D
  Get the currently set x index of the data
getXIndex() - Method in class weka.gui.visualize.VisualizePanel
  Get the index of the attribute on the x axis
getXLabelFreq() - Method in class weka.gui.beans.StripChart
  Get the frequency by which x axis values are printed
getXMLDocument() - Method in class weka.core.xml.XMLOptions
  returns the handler of the XML document.
getXScale() - Method in class weka.gui.visualize.JComponentWriter
  returns the scale factor for the x-axis
getXScale() - Method in class weka.gui.visualize.PrintableComponent
  returns the scale factor for the x-axis
getXScale() - Method in interface weka.gui.visualize.PrintableHandler
  returns the scale factor for the x-axis
getXScale() - Method in class weka.gui.visualize.PrintablePanel
  returns the scale factor for the x-axis
getY() - Method in class weka.classifiers.functions.neural.NeuralConnection
getY() - Method in class weka.gui.beans.BeanInstance
  Gets the y coordinate of this bean
getYindex() - Method in class weka.gui.visualize.PlotData2D
  Get the currently set y index of the data
getYIndex() - Method in class weka.gui.visualize.VisualizePanel
  Get the index of the attribute on the y axis
getYScale() - Method in class weka.gui.visualize.JComponentWriter
  returns the scale factor for the y-axis
getYScale() - Method in class weka.gui.visualize.PrintableComponent
  returns the scale factor for the y-axis
getYScale() - Method in interface weka.gui.visualize.PrintableHandler
  returns the scale factor for the y-axis
getYScale() - Method in class weka.gui.visualize.PrintablePanel
  returns the scale factor for the y-axis
globalBlendTipText() - Method in class weka.classifiers.lazy.KStar
  Returns the tip text for this property
globalInfo() - Method in class weka.associations.Apriori
  Returns a string describing this associator
globalInfo() - Method in class weka.associations.PredictiveApriori
  Returns a string describing this associator
globalInfo() - Method in class weka.associations.Tertius
  Returns a string describing this associator.
globalInfo() - Method in class weka.attributeSelection.BestFirst
  Returns a string describing this search method
globalInfo() - Method in class weka.attributeSelection.CfsSubsetEval
  Returns a string describing this attribute evaluator
globalInfo() - Method in class weka.attributeSelection.ChiSquaredAttributeEval
  Returns a string describing this attribute evaluator
globalInfo() - Method in class weka.attributeSelection.ClassifierSubsetEval
  Returns a string describing this attribute evaluator
globalInfo() - Method in class weka.attributeSelection.ConsistencySubsetEval
  Returns a string describing this search method
globalInfo() - Method in class weka.attributeSelection.ExhaustiveSearch
  Returns a string describing this search method
globalInfo() - Method in class weka.attributeSelection.GainRatioAttributeEval
  Returns a string describing this attribute evaluator
globalInfo() - Method in class weka.attributeSelection.GeneticSearch
  Returns a string describing this search method
globalInfo() - Method in class weka.attributeSelection.GreedyStepwise
  Returns a string describing this search method
globalInfo() - Method in class weka.attributeSelection.InfoGainAttributeEval
  Returns a string describing this attribute evaluator
globalInfo() - Method in class weka.attributeSelection.OneRAttributeEval
  Returns a string describing this attribute evaluator
globalInfo() - Method in class weka.attributeSelection.PrincipalComponents
  Returns a string describing this attribute transformer
globalInfo() - Method in class weka.attributeSelection.RaceSearch
  Returns a string describing this search method
globalInfo() - Method in class weka.attributeSelection.RandomSearch
  Returns a string describing this search method
globalInfo() - Method in class weka.attributeSelection.Ranker
  Returns a string describing this search method
globalInfo() - Method in class weka.attributeSelection.RankSearch
  Returns a string describing this search method
globalInfo() - Method in class weka.attributeSelection.ReliefFAttributeEval
  Returns a string describing this attribute evaluator
globalInfo() - Method in class weka.attributeSelection.SVMAttributeEval
  Returns a string describing this attribute evaluator
globalInfo() - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval
  Returns a string describing this attribute evaluator
globalInfo() - Method in class weka.attributeSelection.WrapperSubsetEval
  Returns a string describing this attribute evaluator
globalInfo() - Method in class weka.classifiers.bayes.AODE
  Returns a string describing this classifier
globalInfo() - Method in class weka.classifiers.bayes.BayesNet
  This will return a string describing the classifier.
globalInfo() - Method in class weka.classifiers.bayes.ComplementNaiveBayes
  Returns a string describing this classifier
globalInfo() - Method in class weka.classifiers.bayes.NaiveBayes
  Returns a string describing this classifier
globalInfo() - Method in class weka.classifiers.bayes.NaiveBayesMultinomial
  Returns a string describing this classifier
globalInfo() - Method in class weka.classifiers.bayes.NaiveBayesSimple
  Returns a string describing this classifier
globalInfo() - Method in class weka.classifiers.bayes.NaiveBayesUpdateable
  Returns a string describing this classifier
globalInfo() - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator
  This will return a string describing the class.
globalInfo() - Method in class weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm
  This will return a string describing the search algorithm.
globalInfo() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
  This will return a string describing the classifier.
globalInfo() - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
  This will return a string describing the search algorithm.
globalInfo() - Method in class weka.classifiers.bayes.net.search.global.HillClimber
  This will return a string describing the search algorithm.
globalInfo() - Method in class weka.classifiers.bayes.net.search.global.K2
  This will return a string describing the search algorithm.
globalInfo() - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber
  This will return a string describing the classifier.
globalInfo() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
  This will return a string describing the classifier.
globalInfo() - Method in class weka.classifiers.bayes.net.search.global.TabuSearch
  This will return a string describing the classifier.
globalInfo() - Method in class weka.classifiers.bayes.net.search.global.TAN
  This will return a string describing the classifier.
globalInfo() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
  This will return a string describing the classifier.
globalInfo() - Method in class weka.classifiers.bayes.net.search.local.HillClimber
  This will return a string describing the search algorithm.
globalInfo() - Method in class weka.classifiers.bayes.net.search.local.K2
  This will return a string describing the search algorithm.
globalInfo() - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber
  This will return a string describing the classifier.
globalInfo() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
  This will return a string describing the classifier.
globalInfo() - Method in class weka.classifiers.bayes.net.search.local.TabuSearch
  This will return a string describing the classifier.
globalInfo() - Method in class weka.classifiers.bayes.net.search.local.TAN
  This will return a string describing the classifier.
globalInfo() - Method in class weka.classifiers.functions.LeastMedSq
  Returns a string describing this classifier
globalInfo() - Method in class weka.classifiers.functions.LinearRegression
  Returns a string describing this classifier
globalInfo() - Method in class weka.classifiers.functions.Logistic
  Returns a string describing this classifier
globalInfo() - Method in class weka.classifiers.functions.MultilayerPerceptron
  This will return a string describing the classifier.
globalInfo() - Method in class weka.classifiers.functions.PaceRegression
  Returns a string describing this classifier
globalInfo() - Method in class weka.classifiers.functions.RBFNetwork
  Returns a string describing this classifier
globalInfo() - Method in class weka.classifiers.functions.SimpleLinearRegression
  Returns a string describing this classifier
globalInfo() - Method in class weka.classifiers.functions.SimpleLogistic
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.functions.SMO
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.functions.SMOreg
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.functions.VotedPerceptron
  Returns a string describing this classifier
globalInfo() - Method in class weka.classifiers.functions.Winnow
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.lazy.IB1
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.lazy.IBk
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.lazy.KStar
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.lazy.LBR
globalInfo() - Method in class weka.classifiers.lazy.LWL
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.meta.AdaBoostM1
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.meta.AdditiveRegression
  Returns a string describing this attribute evaluator
globalInfo() - Method in class weka.classifiers.meta.AttributeSelectedClassifier
  Returns a string describing this search method
globalInfo() - Method in class weka.classifiers.meta.Bagging
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.meta.ClassificationViaRegression
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.meta.CostSensitiveClassifier
globalInfo() - Method in class weka.classifiers.meta.CVParameterSelection
  Returns a string describing this classifier
globalInfo() - Method in class weka.classifiers.meta.Decorate
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.meta.FilteredClassifier
  Returns a string describing this classifier
globalInfo() - Method in class weka.classifiers.meta.Grading
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.meta.LogitBoost
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.meta.MetaCost
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.meta.MultiBoostAB
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.meta.MultiClassClassifier
globalInfo() - Method in class weka.classifiers.meta.MultiScheme
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.meta.OrdinalClassClassifier
  Returns a string describing this attribute evaluator
globalInfo() - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost
globalInfo() - Method in class weka.classifiers.meta.RandomCommittee
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.meta.RegressionByDiscretization
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.meta.Stacking
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.meta.StackingC
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.meta.ThresholdSelector
globalInfo() - Method in class weka.classifiers.meta.Vote
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.misc.HyperPipes
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.misc.VFI
  Returns a string describing this search method
globalInfo() - Method in class weka.classifiers.rules.ConjunctiveRule
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.rules.DecisionTable
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.rules.JRip
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.rules.M5Rules
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.rules.NNge
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.rules.OneR
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.rules.PART
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.rules.Prism
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.rules.Ridor
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.rules.ZeroR
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.trees.ADTree
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.trees.DecisionStump
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.trees.Id3
  Returns a string describing the classifier.
globalInfo() - Method in class weka.classifiers.trees.J48
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.trees.LMT
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.trees.m5.M5Base
  returns information about the classifier
globalInfo() - Method in class weka.classifiers.trees.NBTree
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.trees.RandomForest
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.trees.RandomTree
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.trees.REPTree
  Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.trees.UserClassifier
  This will return a string describing the classifier.
globalInfo() - Method in class weka.clusterers.EM
  Returns a string describing this clusterer
globalInfo() - Method in class weka.clusterers.FarthestFirst
  Returns a string describing this clusterer
globalInfo() - Method in class weka.clusterers.SimpleKMeans
  Returns a string describing this clusterer
globalInfo() - Method in class weka.core.converters.ArffLoader
  Returns a string describing this Loader
globalInfo() - Method in class weka.core.converters.ArffSaver
  Returns a string describing this Saver
globalInfo() - Method in class weka.core.converters.C45Loader
  Returns a string describing this attribute evaluator
globalInfo() - Method in class weka.core.converters.C45Saver
  Returns a string describing this Saver
globalInfo() - Method in class weka.core.converters.CSVLoader
  Returns a string describing this attribute evaluator
globalInfo() - Method in class weka.core.converters.CSVSaver
  Returns a string describing this Saver
globalInfo() - Method in class weka.core.converters.DatabaseLoader
  Returns a string describing this Loader
globalInfo() - Method in class weka.core.converters.DatabaseSaver
  Returns a string describing this Saver
globalInfo() - Method in class weka.core.converters.SerializedInstancesSaver
  Returns a string describing this Saver
globalInfo() - Method in class weka.datagenerators.BIRCHCluster
  Returns a string describing this data generator.
globalInfo() - Method in class weka.datagenerators.RDG1
  Returns a string describing this data generator.
globalInfo() - Method in class weka.experiment.AveragingResultProducer
  Returns a string describing this result producer
globalInfo() - Method in class weka.experiment.ClassifierSplitEvaluator
  Returns a string describing this split evaluator
globalInfo() - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator
  Returns a string describing this split evaluator
globalInfo() - Method in class weka.experiment.CrossValidationResultProducer
  Returns a string describing this result producer
globalInfo() - Method in class weka.experiment.CSVResultListener
  Returns a string describing this result listener
globalInfo() - Method in class weka.experiment.DatabaseResultListener
  Returns a string describing this result listener
globalInfo() - Method in class weka.experiment.DatabaseResultProducer
  Returns a string describing this result producer
globalInfo() - Method in class weka.experiment.InstancesResultListener
  Returns a string describing this result listener
globalInfo() - Method in class weka.experiment.LearningRateResultProducer
  Returns a string describing this result producer
globalInfo() - Method in class weka.experiment.RandomSplitResultProducer
  Returns a string describing this result producer
globalInfo() - Method in class weka.experiment.RegressionSplitEvaluator
  Returns a string describing this split evaluator
globalInfo() - Method in class weka.filters.AllFilter
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.supervised.attribute.AttributeSelection
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.supervised.attribute.ClassOrder
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.supervised.attribute.Discretize
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.supervised.attribute.NominalToBinary
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.supervised.instance.Resample
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.supervised.instance.SpreadSubsample
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.Add
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.AddCluster
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.AddExpression
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.AddNoise
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.ClusterMembership
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.Copy
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.Discretize
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.FirstOrder
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.MakeIndicator
globalInfo() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.NominalToBinary
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.Normalize
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.NumericToBinary
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.NumericTransform
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.Obfuscate
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.RandomProjection
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.Remove
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.RemoveType
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.RemoveUseless
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingValues
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.Standardize
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.StringToNominal
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.SwapValues
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.TimeSeriesDelta
  Returns a string describing this classifier
globalInfo() - Method in class weka.filters.unsupervised.attribute.TimeSeriesTranslate
  Returns a string describing this classifier
globalInfo() - Method in class weka.filters.unsupervised.instance.NonSparseToSparse
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.instance.Normalize
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.instance.Randomize
  Returns a string describing this classifier
globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveFolds
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.instance.RemovePercentage
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveRange
  Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveWithValues
  Returns a string describing this classifier
globalInfo() - Method in class weka.filters.unsupervised.instance.Resample
  Returns a string describing this classifier
globalInfo() - Method in class weka.filters.unsupervised.instance.SparseToNonSparse
  Returns a string describing this filter
globalInfo() - Method in class weka.gui.beans.AttributeSummarizer
  Global info for this bean
globalInfo() - Method in class weka.gui.beans.ClassAssigner
  Global info for this bean
globalInfo() - Method in class weka.gui.beans.Classifier
  Global info (if it exists) for the wrapped classifier
globalInfo() - Method in class weka.gui.beans.ClassifierPerformanceEvaluator
  Global info for this bean
globalInfo() - Method in class weka.gui.beans.ClassValuePicker
  Global info for this bean
globalInfo() - Method in class weka.gui.beans.Clusterer
  Global info (if it exists) for the wrapped classifier
globalInfo() - Method in class weka.gui.beans.ClustererPerformanceEvaluator
  Global info for this bean
globalInfo() - Method in class weka.gui.beans.CrossValidationFoldMaker
  Global info for this bean
globalInfo() - Method in class weka.gui.beans.DataVisualizer
  Global info for this bean
globalInfo() - Method in class weka.gui.beans.Filter
  Global info (if it exists) for the wrapped filter
globalInfo() - Method in class weka.gui.beans.GraphViewer
  Global info for this bean
globalInfo() - Method in class weka.gui.beans.IncrementalClassifierEvaluator
  Global info for this bean
globalInfo() - Method in class weka.gui.beans.Loader
  Global info (if it exists) for the wrapped loader
globalInfo() - Method in class weka.gui.beans.ModelPerformanceChart
  Global info for this bean
globalInfo() - Method in class weka.gui.beans.PredictionAppender
  Global description of this bean
globalInfo() - Method in class weka.gui.beans.Saver
  Global info (if it exists) for the wrapped loader
globalInfo() - Method in class weka.gui.beans.ScatterPlotMatrix
  Global info for this bean
globalInfo() - Method in class weka.gui.beans.StripChart
  Global info for this bean
globalInfo() - Method in class weka.gui.beans.TestSetMaker
  Global info for this bean
globalInfo() - Method in class weka.gui.beans.TextViewer
  Global info for this bean
globalInfo() - Method in class weka.gui.beans.TrainingSetMaker
  Global info for this bean
globalInfo() - Method in class weka.gui.beans.TrainTestSplitMaker
  Global info for this bean
GlobalScoreSearchAlgorithm - Class in weka.classifiers.bayes.net.search.global
  The CVSearchAlgorithm class supports Bayes net structure search algorithms that are based on cross validation (as opposed to for example score based of conditional independence based search algorithms).
GlobalScoreSearchAlgorithm() - Constructor for class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
goDown(String) - Method in class weka.gui.HierarchyPropertyParser
  Go to a certain node of the tree down from the current node according to the specified relative path.
goTo(String) - Method in class weka.gui.HierarchyPropertyParser
  Go to a certain node of the tree according to the specified path Note that the path must be absolute path from the root.
goToChild(String) - Method in class weka.gui.HierarchyPropertyParser
  Go to one child node from the current position in the tree according to the given value
  If the child node with the given value cannot be found it returns false, true otherwise.
goToChild(int) - Method in class weka.gui.HierarchyPropertyParser
  Go to one child node from the current position in the tree according to the given position
goToParent() - Method in class weka.gui.HierarchyPropertyParser
  Go to the parent from the current position in the tree If the current position is the root, it stays there and does not move
goToRoot() - Method in class weka.gui.HierarchyPropertyParser
  Go to the root of the tree
gr(double, double) - Static method in class weka.core.Utils
  Tests if a is greater than b.
Grading - Class in weka.classifiers.meta
  Implements Grading.
Grading() - Constructor for class weka.classifiers.meta.Grading
graph() - Method in class weka.classifiers.bayes.BayesNet
  Returns a BayesNet graph in XMLBIF ver 0.3 format.
graph() - Method in class weka.classifiers.meta.AttributeSelectedClassifier
  Returns graph describing the classifier (if possible).
graph() - Method in class weka.classifiers.meta.CostSensitiveClassifier
  Returns graph describing the classifier (if possible).
graph() - Method in class weka.classifiers.meta.CVParameterSelection
  Returns graph describing the classifier (if possible).
graph() - Method in class weka.classifiers.meta.FilteredClassifier
  Returns graph describing the classifier (if possible).
graph() - Method in class weka.classifiers.meta.ThresholdSelector
  Returns graph describing the classifier (if possible).
graph() - Method in class weka.classifiers.trees.ADTree
  Returns graph describing the tree.
graph() - Method in class weka.classifiers.trees.j48.ClassifierTree
  Returns graph describing the tree.
graph() - Method in class weka.classifiers.trees.J48
  Returns graph describing the tree.
graph() - Method in class weka.classifiers.trees.j48.NBTreeClassifierTree
  Returns graph describing the tree.
graph() - Method in class weka.classifiers.trees.LMT
  Returns graph describing the tree.
graph() - Method in class weka.classifiers.trees.lmt.LMTNode
  Returns graph describing the tree.
graph(StringBuffer) - Method in class weka.classifiers.trees.m5.RuleNode
  Assign a unique identifier to each node in the tree and then calls graphTree
graph() - Method in class weka.classifiers.trees.M5P
  Return a dot style String describing the tree.
graph() - Method in class weka.classifiers.trees.NBTree
  Returns graph describing the tree.
graph() - Method in class weka.classifiers.trees.REPTree
  Outputs the decision tree as a graph
graph() - Method in class weka.classifiers.trees.UserClassifier
graph() - Method in class weka.clusterers.Cobweb
  Generates the graph string of the Cobweb tree
graph() - Method in interface weka.core.Drawable
  Returns a string that describes a graph representing the object.
GraphConstants - Interface in weka.gui.graphvisualizer
  GraphConstants.java
GraphEdge - Class in weka.gui.graphvisualizer
  This class represents an edge in the graph
GraphEdge(int, int, int) - Constructor for class weka.gui.graphvisualizer.GraphEdge
GraphEdge(int, int, int, String, String) - Constructor for class weka.gui.graphvisualizer.GraphEdge
GraphEvent - Class in weka.gui.beans
  Event for graphs
GraphEvent(Object, String, String, int) - Constructor for class weka.gui.beans.GraphEvent
  Creates a new `GraphEvent` instance.
GraphListener - Interface in weka.gui.beans
  Describe interface `TextListener` here.
GraphNode - Class in weka.gui.graphvisualizer
  This class represents a node in the Graph.
GraphNode(String, String) - Constructor for class weka.gui.graphvisualizer.GraphNode
  Constructor
GraphNode(String, String, int) - Constructor for class weka.gui.graphvisualizer.GraphNode
  Constructor
graphType() - Method in class weka.classifiers.bayes.BayesNet
  Returns the type of graph this classifier represents.
graphType() - Method in class weka.classifiers.meta.AttributeSelectedClassifier
  Returns the type of graph this classifier represents.
graphType() - Method in class weka.classifiers.meta.CostSensitiveClassifier
  Returns the type of graph this classifier represents.
graphType() - Method in class weka.classifiers.meta.CVParameterSelection
  Returns the type of graph this classifier represents.
graphType() - Method in class weka.classifiers.meta.FilteredClassifier
  Returns the type of graph this classifier represents.
graphType() - Method in class weka.classifiers.meta.ThresholdSelector
  Returns the type of graph this classifier represents.
graphType() - Method in class weka.classifiers.trees.ADTree
  Returns the type of graph this classifier represents.
graphType() - Method in class weka.classifiers.trees.j48.ClassifierTree
  Returns the type of graph this classifier represents.
graphType() - Method in class weka.classifiers.trees.J48
  Returns the type of graph this classifier represents.
graphType() - Method in class weka.classifiers.trees.LMT
  Returns the type of graph this classifier represents.
graphType() - Method in class weka.classifiers.trees.M5P
  Returns the type of graph this classifier represents.
graphType() - Method in class weka.classifiers.trees.NBTree
  Returns the type of graph this classifier represents.
graphType() - Method in class weka.classifiers.trees.REPTree
  Returns the type of graph this classifier represents.
graphType() - Method in class weka.classifiers.trees.UserClassifier
  Returns the type of graph this classifier represents.
graphType() - Method in class weka.clusterers.Cobweb
  Returns the type of graphs this class represents
graphType() - Method in interface weka.core.Drawable
  Returns the type of graph representing the object.
GraphViewer - Class in weka.gui.beans
  A bean encapsulating weka.gui.treevisualize.TreeVisualizer
GraphViewer() - Constructor for class weka.gui.beans.GraphViewer
GraphViewerBeanInfo - Class in weka.gui.beans
  Bean info class for the graph viewer
GraphViewerBeanInfo() - Constructor for class weka.gui.beans.GraphViewerBeanInfo
GraphVisualizer - Class in weka.gui.graphvisualizer
  This class displays the graph we want to visualize.
GraphVisualizer() - Constructor for class weka.gui.graphvisualizer.GraphVisualizer
  Constructor
  Sets up the gui and initializes all the other previously uninitialized variables.
GreedyStepwise - Class in weka.attributeSelection
  Class for performing a hill climbing search (either forwards or backwards).
GreedyStepwise() - Constructor for class weka.attributeSelection.GreedyStepwise
GRID - Static variable in class weka.datagenerators.BIRCHCluster
grOrEq(double, double) - Static method in class weka.core.Utils
  Tests if a is greater or equal to b.
grouping(boolean) - Method in class weka.classifiers.functions.pace.FlexibleDecimalFormat
grow(Instances) - Method in class weka.classifiers.rules.Rule
  Build this rule
GUIChooser - Class in weka.gui
  The main class for the Weka GUIChooser.
GUIChooser() - Constructor for class weka.gui.GUIChooser
  Creates the experiment environment gui with no initial experiment
GUITipText() - Method in class weka.classifiers.functions.MultilayerPerceptron

## H

h(double) - Method in class weka.classifiers.functions.pace.ChisqMixture
  Computes the value of h(x) given the mixture.
h(DoubleVector) - Method in class weka.classifiers.functions.pace.ChisqMixture
  Computes the value of h(x) given the mixture, where x is a vector.
h(double) - Method in class weka.classifiers.functions.pace.NormalMixture
  Computes the value of h(x) given the mixture.
h(DoubleVector) - Method in class weka.classifiers.functions.pace.NormalMixture
  Computes the value of h(x) given the mixture, where x is a vector.
h1(int, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Constructs single Householder transformation for a column
h2(int, int, double, PaceMatrix, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Performs single Householder transformation on one column of a matrix
hasAntds() - Method in class weka.classifiers.rules.ConjunctiveRule
  Whether this rule has antecedents, i.e.
hasAntds() - Method in class weka.classifiers.rules.Rule
  Whether this rule has antecedents, i.e.
hasFalseHead() - Method in class weka.associations.tertius.Rule
  Test if the head of the rule is false.
hash - Variable in class weka.classifiers.lazy.kstar.KStarCache.TableEntry
  attribute value hash code
hashCode() - Method in class weka.associations.ItemSet
  Produces a hash code for a item set.
hashCode() - Method in class weka.attributeSelection.ConsistencySubsetEval.hashKey
  Calculates a hash code
hashCode() - Method in class weka.classifiers.rules.DecisionTable.hashKey
  Calculates a hash code
hashCode() - Method in class weka.core.SerializedObject
  Returns a hashcode for this object.
hasIncomingBatchInstances() - Method in class weka.gui.beans.Classifier
  Returns true if this classifier has an incoming connection that is a batch set of instances
hasIncomingBatchInstances() - Method in class weka.gui.beans.Clusterer
  Returns true if this clusterer has an incoming connection that is a batch set of instances
hasIncomingStreamInstances() - Method in class weka.gui.beans.Classifier
  Returns true if this classifier has an incoming connection that is an instance stream
hasInterface(Class, Class) - Static method in class weka.core.RTSI
  Checks whether the given class implements the given interface.
hasMaxCounterInstances() - Method in class weka.associations.tertius.LiteralSet
  Test if all the intances are counter-instances.
hasMissingValue() - Method in class weka.core.Instance
  Tests whether an instance has a missing value.
hasModels() - Method in class weka.classifiers.trees.lmt.LMTNode
  Returns true if the logistic regression model at this node has changed compared to the one at the parent node.
hasMoreElements() - Method in class weka.core.FastVector.FastVectorEnumeration
  Tests if there are any more elements to enumerate.
hasMoreIterations() - Method in class weka.experiment.Experiment
  Returns true if there are more iterations to carry out in the experiment.
hasNext() - Method in class weka.associations.tertius.SimpleLinkedList.LinkedListIterator
hasPrevious() - Method in class weka.associations.tertius.SimpleLinkedList.LinkedListInverseIterator
hasTrueBody() - Method in class weka.associations.tertius.Rule
  Test if the body of the rule is true.
hasZeropoint() - Method in class weka.core.Attribute
  Returns whether the attribute has a zeropoint and may be added meaningfully.
Head - Class in weka.associations.tertius
  Class representing the head of a rule.
Head() - Constructor for class weka.associations.tertius.Head
  Constructor without storing the counter-instances.
Head(Instances) - Constructor for class weka.associations.tertius.Head
  Constructor storing the counter-instances.
headContains(Literal) - Method in class weka.associations.tertius.Rule
  Test if the head of the rule contains a literal.
header(int) - Method in class weka.experiment.PairedTTester
  Creates a "header" string describing the current resultsets.
HEIGHT - Static variable in class weka.gui.arffviewer.ArffViewerMainPanel
  default height
heuristicStopTipText() - Method in class weka.classifiers.functions.SimpleLogistic
  Returns the tip text for this property
hf(double) - Method in class weka.classifiers.functions.pace.ChisqMixture
  Computes the value of h(x) / f(x) given the mixture.
hf(double) - Method in class weka.classifiers.functions.pace.NormalMixture
  Computes the value of h(x) / f(x) given the mixture.
hiddenLayersTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
HierarchicalBCEngine - Class in weka.gui.graphvisualizer
  This class lays out the vertices of a graph in a hierarchy of vertical levels, with a number of nodes in each level.
HierarchicalBCEngine(FastVector, FastVector, int, int) - Constructor for class weka.gui.graphvisualizer.HierarchicalBCEngine
  Constructor - takes in FastVectors of nodes and edges, and the initial width and height of a node
HierarchicalBCEngine(FastVector, FastVector, int, int, boolean) - Constructor for class weka.gui.graphvisualizer.HierarchicalBCEngine
  Constructor - takes in FastVectors of nodes and edges, the initial width and height of a node, and a boolean value to indicate if the edges should be concentrated.
HierarchicalBCEngine() - Constructor for class weka.gui.graphvisualizer.HierarchicalBCEngine
  SimpleConstructor If we want to instantiate the class first, and if information for nodes and edges is not available.
HierarchyPropertyParser - Class in weka.gui
  This class implements a parser to read properties that have a hierarchy(i.e.
HierarchyPropertyParser() - Constructor for class weka.gui.HierarchyPropertyParser
  Default constructor
HierarchyPropertyParser(String, String) - Constructor for class weka.gui.HierarchyPropertyParser
  Constructor that builds a tree from the given property with the given delimitor
HillClimber - Class in weka.classifiers.bayes.net.search.global
  HillClimber implements hill climbing using local search for learning Bayesian network.
HillClimber() - Constructor for class weka.classifiers.bayes.net.search.global.HillClimber
HillClimber - Class in weka.classifiers.bayes.net.search.local
  HillClimber implements hill climbing using local search for learning Bayesian network.
HillClimber() - Constructor for class weka.classifiers.bayes.net.search.local.HillClimber
hit(Rectangle, Shape, boolean) - Method in class weka.gui.visualize.PostscriptGraphics
HLINE - Static variable in class weka.gui.visualize.VisualizePanelEvent
holdOutFileTipText() - Method in class weka.attributeSelection.ClassifierSubsetEval
  Returns the tip text for this property
HoldOutSubsetEvaluator - Class in weka.attributeSelection
  Abstract attribute subset evaluator capable of evaluating subsets with respect to a data set that is distinct from that used to initialize/ train the subset evaluator.
HoldOutSubsetEvaluator() - Constructor for class weka.attributeSelection.HoldOutSubsetEvaluator
hornClausesTipText() - Method in class weka.associations.Tertius
  Returns the tip text for this property.
HostListPanel - Class in weka.gui.experiment
  This panel controls setting a list of hosts for a RemoteExperiment to use.
HostListPanel(RemoteExperiment) - Constructor for class weka.gui.experiment.HostListPanel
  Creates the host list panel with the given experiment.
HostListPanel() - Constructor for class weka.gui.experiment.HostListPanel
  Create the host list panel initially disabled.
HyperPipes - Class in weka.classifiers.misc
  Class implementing a HyperPipe classifier.
HyperPipes() - Constructor for class weka.classifiers.misc.HyperPipes
hypot(double, double) - Static method in class weka.classifiers.functions.pace.Maths
  sqrt(a^2 + b^2) without under/overflow.
hypot(double, double) - Static method in class weka.core.matrix.Maths
  sqrt(a^2 + b^2) without under/overflow.

## I

IB1 - Class in weka.classifiers.lazy
  IB1-type classifier.
IB1() - Constructor for class weka.classifiers.lazy.IB1
IBk - Class in weka.classifiers.lazy
  K-nearest neighbours classifier.
IBk(int) - Constructor for class weka.classifiers.lazy.IBk
  IBk classifier.
IBk() - Constructor for class weka.classifiers.lazy.IBk
  IB1 classifer.
ICON_PATH - Static variable in class weka.gui.beans.BeanVisual
ICSSearchAlgorithm - Class in weka.classifiers.bayes.net.search.ci
  ICSSearchAlgorithm implements Conditional Independence based search algorithm for Bayes Network structure learning.
ICSSearchAlgorithm() - Constructor for class weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm
Id3 - Class in weka.classifiers.trees
  Class implementing an Id3 decision tree classifier.
Id3() - Constructor for class weka.classifiers.trees.Id3
identity(int, int) - Static method in class weka.classifiers.functions.pace.Matrix
  Generate identity matrix
identity(int, int) - Static method in class weka.core.matrix.Matrix
  Generate identity matrix
IDFTransformTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Returns the tip text for this property
IDLE - Static variable in class weka.gui.beans.BeanInstance
ignored() - Method in class weka.core.xml.PropertyHandler
  returns an enumeration of the stored display names and classes of properties to ignore.
  NOTE: String and Class Objects are mixed in this enumeration, depending whether it is a global property to ignore or just one for a certain class!
ignoredAttributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.AddCluster
  Returns the tip text for this property
ignoredAttributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.ClusterMembership
  Returns the tip text for this property
IMAGES - Static variable in class weka.gui.ComponentHelper
  the default directories for images
IMPLICIT - Static variable in class weka.associations.Tertius
Impurity - Class in weka.classifiers.trees.m5
  Class for handling the impurity values when spliting the instances
Impurity(int, int, Instances, int) - Constructor for class weka.classifiers.trees.m5.Impurity
  Constructs an Impurity object containing the impurity values of partitioning the instances using an attribute
incompleteBeta(double, double, double) - Static method in class weka.core.Statistics
  Returns the Incomplete Beta Function evaluated from zero to `xx`.
incorrect() - Method in class weka.classifiers.evaluation.ConfusionMatrix
  Gets the number of incorrect classifications (that is, for which an incorrect prediction was made).
incorrect() - Method in class weka.classifiers.Evaluation
  Gets the number of instances incorrectly classified (that is, for which an incorrect prediction was made).
incremental(double, int) - Method in class weka.classifiers.trees.m5.Impurity
  Incrementally computes the impurirty values
INCREMENTAL - Static variable in interface weka.core.converters.Saver
IncrementalClassifierEvaluator - Class in weka.gui.beans
  Bean that evaluates incremental classifiers
IncrementalClassifierEvaluator() - Constructor for class weka.gui.beans.IncrementalClassifierEvaluator
IncrementalClassifierEvaluatorBeanInfo - Class in weka.gui.beans
  Bean info class for the incremental classifier evaluator bean
IncrementalClassifierEvaluatorBeanInfo() - Constructor for class weka.gui.beans.IncrementalClassifierEvaluatorBeanInfo
IncrementalClassifierEvent - Class in weka.gui.beans
  Class encapsulating an incrementally built classifier and current instance
IncrementalClassifierEvent(Object, Classifier, Instance, int) - Constructor for class weka.gui.beans.IncrementalClassifierEvent
  Creates a new `IncrementalClassifierEvent` instance.
IncrementalClassifierEvent(Object, Classifier, Instances) - Constructor for class weka.gui.beans.IncrementalClassifierEvent
  Creates a new incremental classifier event that encapsulates header information and classifier.
IncrementalClassifierEvent(Object) - Constructor for class weka.gui.beans.IncrementalClassifierEvent
IncrementalClassifierListener - Interface in weka.gui.beans
  Interface to something that can process a IncrementalClassifierEvent
IncrementalConverter - Interface in weka.core.converters
  Marker interface for a loader/saver that can retrieve instances incrementally
index() - Method in class weka.core.Attribute
  Returns the index of this attribute.
index(int) - Method in class weka.core.Instance
  Returns the index of the attribute stored at the given position.
index(int) - Method in class weka.core.SparseInstance
  Returns the index of the attribute stored at the given position.
INDEX_BEANCONNECTIONS - Static variable in class weka.gui.beans.xml.XMLBeans
  the index in the Vector, where the BeanConnections are stored (Instances and Connections are stored in a Vector and then serialized)
INDEX_BEANINSTANCES - Static variable in class weka.gui.beans.xml.XMLBeans
  the index in the Vector, where the BeanInstances are stored (Instances and Connections are stored in a Vector and then serialized)
indexOf(Literal) - Method in class weka.associations.tertius.Predicate
indexOf(Object) - Method in class weka.core.FastVector
  Searches for the first occurence of the given argument, testing for equality using the equals method.
indexOfMax() - Method in class weka.classifiers.functions.pace.DoubleVector
  Returns the index of the maximum.
indexOfValue(String) - Method in class weka.core.Attribute
  Returns the index of a given attribute value.
indexToString(int) - Static method in class weka.core.SingleIndex
  Creates a string representation of the given index.
indicesToRangeList(int[]) - Static method in class weka.core.Range
  Creates a string representation of the indices in the supplied array.
INDIVIDUAL_PROPERTY - Static variable in class weka.associations.tertius.IndividualLiteral
IndividualInstance - Class in weka.associations.tertius
IndividualInstance(Instance, Instances) - Constructor for class weka.associations.tertius.IndividualInstance
IndividualInstance(IndividualInstance) - Constructor for class weka.associations.tertius.IndividualInstance
IndividualInstances - Class in weka.associations.tertius
IndividualInstances(Instances, Instances) - Constructor for class weka.associations.tertius.IndividualInstances
IndividualLiteral - Class in weka.associations.tertius
IndividualLiteral(Predicate, String, int, int, int, int) - Constructor for class weka.associations.tertius.IndividualLiteral
individualPredictions(Instance) - Method in class weka.classifiers.meta.MultiClassClassifier
  Returns the individual predictions of the base classifiers for an instance.
info(int[]) - Static method in class weka.core.Utils
  Computes entropy for an array of integers.
infoGain() - Method in class weka.classifiers.trees.j48.BinC45Split
  Returns (C4.5-type) information gain for the generated split.
infoGain() - Method in class weka.classifiers.trees.j48.C45Split
  Returns (C4.5-type) information gain for the generated split.
InfoGainAttributeEval - Class in weka.attributeSelection
  Class for Evaluating attributes individually by measuring information gain with respect to the class.
InfoGainAttributeEval() - Constructor for class weka.attributeSelection.InfoGainAttributeEval
  Constructor
InfoGainSplitCrit - Class in weka.classifiers.trees.j48
  Class for computing the information gain for a given distribution.
InfoGainSplitCrit() - Constructor for class weka.classifiers.trees.j48.InfoGainSplitCrit
Init(int, int) - Method in class weka.classifiers.bayes.net.BayesNetGenerator
initAsNaiveBayesTipText() - Method in class weka.classifiers.bayes.net.search.SearchAlgorithm
initClassifier(Instances) - Method in interface weka.classifiers.IterativeClassifier
  Inits an iterative classifier.
initClassifier(Instances) - Method in class weka.classifiers.trees.ADTree
  Sets up the tree ready to be trained, using two-class optimized method.
initCPTs() - Method in class weka.classifiers.bayes.BayesNet
initCPTs(BayesNet) - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator
  initCPTs reserves space for CPTs and set all counts to zero
initCPTs(BayesNet) - Method in class weka.classifiers.bayes.net.estimate.BMAEstimator
  initCPTs reserves space for CPTs and set all counts to zero
initCPTs(BayesNet) - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator
  initCPTs reserves space for CPTs and set all counts to zero
initCPTs(BayesNet) - Method in class weka.classifiers.bayes.net.estimate.SimpleEstimator
  initCPTs reserves space for CPTs and set all counts to zero
INITIAL_STEP - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
initialize() - Method in class weka.classifiers.CostMatrix
  Sets the cost of all correct classifications to 0, and all misclassifications to 1.
initialize() - Method in class weka.classifiers.trees.j48.Distribution
  Sets all counts to zero.
initialize(int, int, int) - Method in class weka.classifiers.trees.m5.CorrelationSplitInfo
  Resets the object of split information
initialize(int, int, int) - Method in class weka.classifiers.trees.m5.YongSplitInfo
  Resets the object of split information
initialize() - Method in class weka.experiment.Experiment
  Prepares an experiment for running, initializing current iterator settings.
initialize() - Method in class weka.experiment.RemoteExperiment
  Prepares a remote experiment for running, creates sub experiments
initialize() - Method in class weka.gui.visualize.JPEGWriter
  further initialization
initInternalFields() - Method in class weka.gui.visualize.MatrixPanel
  Initializes internal data fields, i.e.
initStructure() - Method in class weka.classifiers.bayes.BayesNet
  Init structure initializes the structure to an empty graph or a Naive Bayes graph (depending on the -N flag).
innerProduct(DoubleVector) - Method in class weka.classifiers.functions.pace.DoubleVector
  Returns the inner product of two DoubleVectors
INPUT - Static variable in class weka.classifiers.functions.neural.NeuralConnection
  This unit is an input unit.
input(Instance) - Method in class weka.filters.AllFilter
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.Filter
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.NullFilter
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.supervised.attribute.AttributeSelection
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.supervised.attribute.ClassOrder
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.supervised.attribute.Discretize
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.supervised.attribute.NominalToBinary
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.supervised.instance.Resample
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.supervised.instance.SpreadSubsample
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.Add
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.AddCluster
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.AddExpression
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.AddNoise
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat
  {@inheritDoc
input(Instance) - Method in class weka.filters.unsupervised.attribute.ClusterMembership
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.Copy
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.Discretize
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.FirstOrder
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.MakeIndicator
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.MergeTwoValues
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.NominalToBinary
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.Normalize
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.NumericToBinary
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.NumericTransform
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.Obfuscate
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.RandomProjection
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.Remove
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.RemoveType
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.RemoveUseless
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.ReplaceMissingValues
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.Standardize
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.StringToNominal
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.SwapValues
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.instance.NonSparseToSparse
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.instance.Normalize
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.instance.Randomize
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.instance.RemoveFolds
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.instance.RemoveMisclassified
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.instance.RemovePercentage
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.instance.RemoveRange
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.instance.RemoveWithValues
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.instance.Resample
  Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.instance.SparseToNonSparse
  Input an instance for filtering.
input(Instance) - Method in class weka.gui.streams.InstanceCounter
input(Instance) - Method in class weka.gui.streams.InstanceJoiner
input(Instance) - Method in class weka.gui.streams.InstanceSavePanel
input(Instance) - Method in class weka.gui.streams.InstanceTable
input(Instance) - Method in class weka.gui.streams.InstanceViewer
inputFormat(Instances) - Method in class weka.filters.Filter
  Deprecated. use `setInputFormat(Instances)` instead.
inputFormat(Instances) - Method in class weka.gui.streams.InstanceCounter
inputFormat(Instances) - Method in class weka.gui.streams.InstanceJoiner
  Sets the format of the input instances.
inputFormat(Instances) - Method in class weka.gui.streams.InstanceSavePanel
inputFormat(Instances) - Method in class weka.gui.streams.InstanceTable
inputFormat(Instances) - Method in class weka.gui.streams.InstanceViewer
inputs(Vector) - Static method in class weka.gui.beans.BeanConnection
  Returns a vector of BeanInstances that can be considered as inputs (or the left-hand side of a sub-flow)
insert(int) - Method in class weka.classifiers.functions.supportVector.SMOset
  Inserts an element into the set.
insert(double, double, double) - Method in class weka.classifiers.lazy.kstar.KStarCache.CacheTable
  Inserts a new entry in the hashtable using the specified key.
insertAttributeAt(int) - Method in class weka.core.Instance
  Inserts an attribute at the given position (0 to numAttributes()).
insertAttributeAt(Attribute, int) - Method in class weka.core.Instances
  Inserts an attribute at the given position (0 to numAttributes()) and sets all values to be missing.
insertElementAt(Object, int) - Method in class weka.core.FastVector
  Inserts an element at the given position.
installLinearModels() - Method in class weka.classifiers.trees.m5.RuleNode
  Traverses the tree and installs linear models at each node.
installSmoothedModels() - Method in class weka.classifiers.trees.m5.RuleNode
Instance - Class in weka.core
  Class for handling an instance.
Instance(double, double[]) - Constructor for class weka.core.Instance
  Constructor that inititalizes instance variable with given values.
Instance(int) - Constructor for class weka.core.Instance
  Constructor of an instance that sets weight to one, all values to be missing, and the reference to the dataset to null.
instance(int) - Method in class weka.core.Instances
  Returns the instance at the given position.
INSTANCE_AVAILABLE - Static variable in class weka.gui.beans.InstanceEvent
INSTANCE_AVAILABLE - Static variable in class weka.gui.streams.InstanceEvent
  Specifies that an instance is available
InstanceComparator - Class in weka.core
  A comparator for the Instance class.
InstanceComparator() - Constructor for class weka.core.InstanceComparator
  initializes the comparator and includes the class in the comparison
InstanceComparator(boolean) - Constructor for class weka.core.InstanceComparator
  initializes the comparator
InstanceCounter - Class in weka.gui.streams
  A bean that counts instances streamed to it.
InstanceCounter() - Constructor for class weka.gui.streams.InstanceCounter
InstanceEvent - Class in weka.gui.beans
  Event that encapsulates a single instance or header information only
InstanceEvent(Object, Instance, int) - Constructor for class weka.gui.beans.InstanceEvent
  Creates a new `InstanceEvent` instance that encapsulates a single instance only.
InstanceEvent(Object, Instances) - Constructor for class weka.gui.beans.InstanceEvent
  Creates a new `InstanceEvent` instance which encapsulates header information only.
InstanceEvent(Object) - Constructor for class weka.gui.beans.InstanceEvent
InstanceEvent - Class in weka.gui.streams
  An event encapsulating an instance stream event.
InstanceEvent(Object, int) - Constructor for class weka.gui.streams.InstanceEvent
  Constructs an InstanceEvent with the specified source object and event type
InstanceJoiner - Class in weka.gui.streams
  A bean that joins two streams of instances into one.
InstanceJoiner() - Constructor for class weka.gui.streams.InstanceJoiner
  Setup the initial states of the member variables
InstanceListener - Interface in weka.gui.beans
  Interface to something that can accept instance events
InstanceListener - Interface in weka.gui.streams
  An interface for objects interested in listening to streams of instances.
InstanceLoader - Class in weka.gui.streams
  A bean that produces a stream of instances from a file.
InstanceLoader() - Constructor for class weka.gui.streams.InstanceLoader
instanceProduced(InstanceEvent) - Method in class weka.gui.streams.InstanceCounter
instanceProduced(InstanceEvent) - Method in class weka.gui.streams.InstanceJoiner
instanceProduced(InstanceEvent) - Method in interface weka.gui.streams.InstanceListener
instanceProduced(InstanceEvent) - Method in class weka.gui.streams.InstanceSavePanel
instanceProduced(InstanceEvent) - Method in class weka.gui.streams.InstanceTable
instanceProduced(InstanceEvent) - Method in class weka.gui.streams.InstanceViewer
InstanceProducer - Interface in weka.gui.streams
  An interface for objects capable of producing streams of instances.
InstanceQuery - Class in weka.experiment
  Convert the results of a database query into instances.
InstanceQuery() - Constructor for class weka.experiment.InstanceQuery
  Sets up the database drivers
instanceRangeTipText() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries
  Returns the tip text for this property
Instances - Class in weka.core
  Class for handling an ordered set of weighted instances.
Instances(Reader) - Constructor for class weka.core.Instances
  Reads an ARFF file from a reader, and assigns a weight of one to each instance.
Instances(Reader, int) - Constructor for class weka.core.Instances
  Reads the header of an ARFF file from a reader and reserves space for the given number of instances.
Instances(Instances) - Constructor for class weka.core.Instances
  Constructor copying all instances and references to the header information from the given set of instances.
Instances(Instances, int) - Constructor for class weka.core.Instances
  Constructor creating an empty set of instances.
Instances(Instances, int, int) - Constructor for class weka.core.Instances
  Creates a new set of instances by copying a subset of another set.
Instances(String, FastVector, int) - Constructor for class weka.core.Instances
  Creates an empty set of instances.
InstanceSavePanel - Class in weka.gui.streams
  A bean that saves a stream of instances to a file.
InstanceSavePanel() - Constructor for class weka.gui.streams.InstanceSavePanel
instancesDownBranch(int, Instances) - Method in class weka.classifiers.trees.adtree.Splitter
  Gets the subset of instances that apply to a particluar branch of the split.
instancesDownBranch(int, Instances) - Method in class weka.classifiers.trees.adtree.TwoWayNominalSplit
  Gets the subset of instances that apply to a particluar branch of the split.
instancesDownBranch(int, Instances) - Method in class weka.classifiers.trees.adtree.TwoWayNumericSplit
  Gets the subset of instances that apply to a particluar branch of the split.
instancesIndicesTipText() - Method in class weka.filters.unsupervised.instance.RemoveRange
  Returns the tip text for this property
InstancesResultListener - Class in weka.experiment
  InstancesResultListener outputs the received results in arff format to a Writer.
InstancesResultListener() - Constructor for class weka.experiment.InstancesResultListener
  Sets temporary file.
InstancesSummaryPanel - Class in weka.gui
  This panel just displays relation name, number of instances, and number of attributes.
InstancesSummaryPanel() - Constructor for class weka.gui.InstancesSummaryPanel
  Creates the instances panel with no initial instances.
InstanceTable - Class in weka.gui.streams
  A bean that takes a stream of instances and displays in a table.
InstanceTable() - Constructor for class weka.gui.streams.InstanceTable
InstanceViewer - Class in weka.gui.streams
  This is a very simple instance viewer - just displays the dataset as text output as it would be written to a file.
InstanceViewer() - Constructor for class weka.gui.streams.InstanceViewer
intCount - Variable in class weka.core.AttributeStats
  The number of int-like values
INTEGER - Static variable in class weka.core.converters.DatabaseLoader
INTEGER - Static variable in class weka.experiment.DatabaseUtils
  Type mapping for INTEGER used for reading experiment results
intercept() - Method in class weka.classifiers.trees.m5.PreConstructedLinearModel
  Return the intercept
IntVector - Class in weka.classifiers.functions.pace
IntVector() - Constructor for class weka.classifiers.functions.pace.IntVector
  Constructs a null vector.
IntVector(int) - Constructor for class weka.classifiers.functions.pace.IntVector
  Constructs an n-vector of zeros.
IntVector(int, int) - Constructor for class weka.classifiers.functions.pace.IntVector
  Constructs an n-vector of a constant
IntVector(int[]) - Constructor for class weka.classifiers.functions.pace.IntVector
  Constructs a vector given an int array
inverse() - Method in class weka.core.matrix.Matrix
  Matrix inverse or pseudoinverse
inverseIterator() - Method in class weka.associations.tertius.SimpleLinkedList
invertSelectionTipText() - Method in class weka.filters.supervised.attribute.Discretize
  Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds
  Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries
  Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.Copy
  Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.Discretize
  Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.NominalToBinary
  Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.NumericTransform
  Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.Remove
  Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.RemoveType
  Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.instance.RemoveFolds
  Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.instance.RemovePercentage
  Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.instance.RemoveRange
  Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithValues
  Returns the tip text for this property
invertTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified
  Returns the tip text for this property
invokeMain(String, String[]) - Static method in class weka.gui.SplashWindow
  Invokes the main method of the provided class name.
invokeMethod(String, String, String[]) - Static method in class weka.gui.SplashWindow
  Invokes the named method of the provided class name.
isAllowed(Class, String) - Method in class weka.core.xml.PropertyHandler
  returns whether the given property (display name) is allowed for the given class.
isAllowed(Object, String) - Method in class weka.core.xml.PropertyHandler
  returns whether the given property (display name) is allowed for the given object .
isAveragable() - Method in class weka.core.Attribute
  Returns whether the attribute can be averaged meaningfully.
isCellEditable(int, int) - Method in class weka.gui.arffviewer.ArffTableModel
  returns true if the cell at rowindex and columnindexis editable
isCellEditable(int, int) - Method in class weka.gui.TableMap
isChanged() - Method in class weka.gui.arffviewer.ArffPanel
  returns whether the content of the panel was changed
isClass() - Method in class weka.associations.tertius.Predicate
isConnected() - Method in class weka.experiment.DatabaseUtils
  Returns true if a database connection is active.
isCover(Instance) - Method in class weka.classifiers.rules.ConjunctiveRule
  Whether the instance covered by this rule
isDate() - Method in class weka.core.Attribute
  Tests if the attribute is a date type.
isEmpty() - Method in class weka.associations.tertius.LiteralSet
  Test if this set is empty.
isEmpty() - Method in class weka.associations.tertius.Rule
  Test if this rule is empty.
isEmpty() - Method in class weka.associations.tertius.SimpleLinkedList
isEmpty() - Method in class weka.classifiers.functions.pace.DiscreteFunction
  Returns true if it is empty.
isEmpty() - Method in class weka.classifiers.functions.pace.DoubleVector
  Checks if it is an empty vector
isEmpty() - Method in class weka.classifiers.functions.pace.IntVector
  Returns true if the vector is empty
isEmpty() - Method in class weka.classifiers.functions.pace.PaceMatrix
  Check if the matrix is empty
isEmpty() - Method in class weka.classifiers.lazy.kstar.KStarCache.CacheTable
  Tests if this hashtable maps no keys to values.
isEnabled() - Method in class weka.core.Memory
  returns whether the memory management is enabled
isFullRank() - Method in class weka.core.matrix.QRDecomposition
  Is the matrix full rank?
isHidden() - Method in class weka.gui.beans.BeanConnection
  Returns true if this connection is invisible
isHierachic(String) - Method in class weka.gui.HierarchyPropertyParser
  Whether the given string has a hierachy structure with the seperators
isIgnored(String) - Method in class weka.core.xml.PropertyHandler
  checks whether the given display name is an ignored property
isIgnored(Class, String) - Method in class weka.core.xml.PropertyHandler
  checks whether the given display name of a certain class is an ignored property.
isIgnored(Object, String) - Method in class weka.core.xml.PropertyHandler
  checks whether the given display name of a given object is an ignored property.
isIncludedIn(Rule) - Method in class weka.associations.tertius.Body
  Test if this Body is included in a rule.
isIncludedIn(Rule) - Method in class weka.associations.tertius.Head
  Test if this Head is included in a rule.
isIncludedIn(Rule) - Method in class weka.associations.tertius.LiteralSet
  Test if this LiteralSet is included in a rule.
isInRange(double) - Method in class weka.core.Attribute
  Determines whether a value lies within the bounds of the attribute.
isInRange(int) - Method in class weka.core.Range
  Gets whether the supplied cardinal number is included in the current range.
isKOML(String) - Static method in class weka.core.xml.SerialUIDChanger
  checks whether the given filename ends with ".koml"
isLeaf() - Method in class weka.classifiers.trees.m5.RuleNode
  Return true if this node is a leaf
isLeafReached() - Method in class weka.gui.HierarchyPropertyParser
  Whether the current position is a leaf
isMissing(int) - Method in class weka.core.Instance
  Tests if a specific value is "missing".
isMissing(Attribute) - Method in class weka.core.Instance
  Tests if a specific value is "missing".
isMissing(int) - Method in class weka.core.SparseInstance
  Tests if a specific value is "missing".
isMissingAt(int, int) - Method in class weka.gui.arffviewer.ArffTableModel
  checks whether the value at the given position is missing
isMissingAt(int, int) - Method in class weka.gui.arffviewer.ArffTableSorter
  checks whether the value at the given position is missing
isMissingSparse(int) - Method in class weka.core.Instance
  Tests if a specific value is "missing".
isMissingValue(double) - Static method in class weka.core.Instance
  Tests if the given value codes "missing".
isNewer(Object) - Method in class weka.core.Version
  checks whether this version is newer than the one from the given version string
isNominal() - Method in class weka.core.Attribute
  Test if the attribute is nominal.
isNominal() - Method in class weka.filters.unsupervised.instance.RemoveWithValues
  Returns true if selection attribute is nominal.
isNonsingular() - Method in class weka.core.matrix.LUDecomposition
  Is the matrix nonsingular?
isNotificationEnabled() - Method in class weka.gui.arffviewer.ArffTableModel
  returns whether the notification of changes is enabled
isNotificationEnabled() - Method in class weka.gui.arffviewer.ArffTableSorter
  returns whether the notification of changes is enabled
isNumeric() - Method in class weka.core.Attribute
  Tests if the attribute is numeric.
isNumeric() - Method in class weka.filters.unsupervised.instance.RemoveWithValues
  Returns true if selection attribute is numeric.
isOlder(Object) - Method in class weka.core.Version
  checks whether this version is older than the one from the given version string
isOutOfMemory() - Method in class weka.core.Memory
  checks if there's still enough memory left.
isOutputFormatDefined() - Method in class weka.filters.Filter
  Returns whether the output format is ready to be collected
isOutputFormatDefined() - Method in class weka.filters.unsupervised.attribute.RemoveType
  Returns whether the output format is ready to be collected
isPaintable() - Method in class weka.gui.CostMatrixEditor
  Indicates whether the object can be represented graphically.
isPaintable() - Method in class weka.gui.FileEditor
  Returns true since this editor is paintable.
isPaintable() - Method in class weka.gui.GenericArrayEditor
  Returns true to indicate that we can paint a representation of the string array
isPaintable() - Method in class weka.gui.GenericObjectEditor
  Returns true to indicate that we can paint a representation of the Object.
isPaintable() - Method in class weka.gui.SimpleDateFormatEditor
  Indicates whether the object can be represented graphically.
isPanelSelected() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  checks whether a panel is currently selected
isPresent() - Static method in class weka.core.xml.KOML
  returns whether KOML is present or not, i.e.
isRegular() - Method in class weka.core.Attribute
  Returns whether the attribute values are equally spaced.
isResultRequired(ResultProducer, Object[]) - Method in class weka.experiment.AveragingResultProducer
  Determines whether the results for a specified key must be generated.
isResultRequired(ResultProducer, Object[]) - Method in class weka.experiment.CSVResultListener
  Always says a result is required.
isResultRequired(ResultProducer, Object[]) - Method in class weka.experiment.DatabaseResultListener
  Always says a result is required.
isResultRequired(ResultProducer, Object[]) - Method in class weka.experiment.DatabaseResultProducer
  Determines whether the results for a specified key must be generated.
isResultRequired(ResultProducer, Object[]) - Method in class weka.experiment.LearningRateResultProducer
  Determines whether the results for a specified key must be generated.
isResultRequired(ResultProducer, Object[]) - Method in interface weka.experiment.ResultListener
  Determines whether the results for a specified key must be generated.
isRootReached() - Method in class weka.gui.HierarchyPropertyParser
  Whether the current position is the root
isSequentialAttIndexValid() - Method in class weka.classifiers.lazy.LBR.Indexes
  Returns whether or not the Sequential Attribute Index requires rebuilding due to a change
isSequentialInstanceIndexValid() - Method in class weka.classifiers.lazy.LBR.Indexes
  Returns whether or not the Sequential Instance Index requires rebuilding due to a change
isSPD() - Method in class weka.core.matrix.CholeskyDecomposition
  Is the matrix symmetric and positive definite?
isSquare() - Method in class weka.core.matrix.Matrix
  returns whether the matrix is a square matrix or not.
isStopword(String) - Static method in class weka.core.Stopwords
  Returns true if the given string is a stop word.
isString() - Method in class weka.core.Attribute
  Tests if the attribute is a string.
isStructureOnly() - Method in class weka.gui.beans.DataSetEvent
  Returns true if the encapsulated instances contain just header information
isStructureOnly() - Method in class weka.gui.beans.TestSetEvent
  Returns true if the encapsulated instances contain just header information
isStructureOnly() - Method in class weka.gui.beans.TrainingSetEvent
  Returns true if the encapsulated instances contain just header information
isSubclass(Class, Class) - Static method in class weka.core.RTSI
  Checks whether the "otherclass" is a subclass of the given "superclass".
isSymmetric() - Method in class weka.core.Matrix
  Deprecated. Returns true if the matrix is symmetric.
isSymmetric() - Method in class weka.core.matrix.Matrix
  Returns true if the matrix is symmetric.
isUndoEnabled() - Method in interface weka.core.Undoable
  returns whether undo support is enabled
isUndoEnabled() - Method in class weka.gui.arffviewer.ArffPanel
  returns whether undo support is enabled
isUndoEnabled() - Method in class weka.gui.arffviewer.ArffTableModel
  returns whether undo support is enabled
isUndoEnabled() - Method in class weka.gui.arffviewer.ArffTableSorter
  returns whether undo support is enabled
isUseK2Prior() - Method in class weka.classifiers.bayes.net.estimate.BMAEstimator
isUseK2Prior() - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator
itemAt(int) - Method in class weka.associations.ItemSet
  Gest the index of the value of the specified attribute
items() - Method in class weka.associations.ItemSet
  Gest the item set as an int array
ItemSet - Class in weka.associations
  Class for storing a set of items.
ItemSet(int) - Constructor for class weka.associations.ItemSet
  Constructor
ItemSet(int, int[]) - Constructor for class weka.associations.ItemSet
  Constructor
ItemSet(int[]) - Constructor for class weka.associations.ItemSet
  Contsructor
itemStateChanged(ItemEvent) - Method in class weka.gui.treevisualizer.TreeVisualizer
  Performs the action associated with the ItemEvent.
IteratedSingleClassifierEnhancer - Class in weka.classifiers
  Abstract utility class for handling settings common to meta classifiers that build an ensemble from a single base learner.
IteratedSingleClassifierEnhancer() - Constructor for class weka.classifiers.IteratedSingleClassifierEnhancer
IterativeClassifier - Interface in weka.classifiers
  Interface for classifiers that can induce models of growing complexity one step at a time.
iterator() - Method in class weka.associations.tertius.SimpleLinkedList

## J

J48 - Class in weka.classifiers.trees
  Class for generating an unpruned or a pruned C4.5 decision tree.
J48() - Constructor for class weka.classifiers.trees.J48
JComponentWriter - Class in weka.gui.visualize
  This class takes any JComponent and outputs it to a file.
JComponentWriter() - Constructor for class weka.gui.visualize.JComponentWriter
  initializes the object
JComponentWriter(JComponent) - Constructor for class weka.gui.visualize.JComponentWriter
  initializes the object with the given Component
JComponentWriter(JComponent, File) - Constructor for class weka.gui.visualize.JComponentWriter
  initializes the object with the given Component and filename
joinOptions(String[]) - Static method in class weka.core.Utils
  Joins all the options in an option array into a single string, as might be used on the command line.
JPEGWriter - Class in weka.gui.visualize
  This class takes any JComponent and outputs it to a JPEG-file.
JPEGWriter() - Constructor for class weka.gui.visualize.JPEGWriter
  initializes the object
JPEGWriter(JComponent) - Constructor for class weka.gui.visualize.JPEGWriter
  initializes the object with the given Component
JPEGWriter(JComponent, File) - Constructor for class weka.gui.visualize.JPEGWriter
  initializes the object with the given Component and filename
JRip - Class in weka.classifiers.rules
  This class implements a propositional rule learner, Repeated Incremental Pruning to Produce Error Reduction (RIPPER), which is proposed by William W.
JRip() - Constructor for class weka.classifiers.rules.JRip
JTableHelper - Class in weka.gui
  A helper class for JTable, e.g.
JTableHelper(JTable) - Constructor for class weka.gui.JTableHelper
  initializes the object

## K

K2 - Class in weka.classifiers.bayes.net.search.global
  Class for a Bayes Network classifier based on K2 for learning structure.
K2() - Constructor for class weka.classifiers.bayes.net.search.global.K2
K2 - Class in weka.classifiers.bayes.net.search.local
  Class for a Bayes Network classifier based on K2 for learning structure.
K2() - Constructor for class weka.classifiers.bayes.net.search.local.K2
kappa() - Method in class weka.classifiers.Evaluation
  Returns value of kappa statistic if class is nominal.
KBInformation() - Method in class weka.classifiers.Evaluation
  Return the total Kononenko & Bratko Information score in bits
KBMeanInformation() - Method in class weka.classifiers.Evaluation
  Return the Kononenko & Bratko Information score in bits per instance.
KBRelativeInformation() - Method in class weka.classifiers.Evaluation
  Return the Kononenko & Bratko Relative Information score
KDConditionalEstimator - Class in weka.estimators
  Conditional probability estimator for a numeric domain conditional upon a discrete domain (utilises separate kernel estimators for each discrete conditioning value).
KDConditionalEstimator(int, double) - Constructor for class weka.estimators.KDConditionalEstimator
  Constructor
KDDataGenerator - Class in weka.gui.boundaryvisualizer
  KDDataGenerator.
KDDataGenerator() - Constructor for class weka.gui.boundaryvisualizer.KDDataGenerator
Kernel - Class in weka.classifiers.functions.supportVector
  Abstract kernel.
Kernel() - Constructor for class weka.classifiers.functions.supportVector.Kernel
KernelEstimator - Class in weka.estimators
  Simple kernel density estimator.
KernelEstimator(double) - Constructor for class weka.estimators.KernelEstimator
  Constructor that takes a precision argument.
key - Variable in class weka.classifiers.lazy.kstar.KStarCache.TableEntry
  attribute value
keyFieldNameTipText() - Method in class weka.experiment.AveragingResultProducer
  Returns the tip text for this property
keys() - Method in class weka.core.xml.MethodHandler
  returns an enumeration over all currently stored custom methods, i.e.
keysTipText() - Method in class weka.core.converters.DatabaseLoader
  the tip text for this property
kFoldCV(BayesNet, int) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
  kFoldCV uses k-fold cross validation to measure the accuracy of a Bayes network classifier.
KKConditionalEstimator - Class in weka.estimators
  Conditional probability estimator for a numeric domain conditional upon a numeric domain.
KKConditionalEstimator(double) - Constructor for class weka.estimators.KKConditionalEstimator
  Constructor
KNNTipText() - Method in class weka.classifiers.lazy.IBk
  Returns the tip text for this property
KNNTipText() - Method in class weka.classifiers.lazy.LWL
  Returns the tip text for this property
KnowledgeFlow - Class in weka.gui.beans
  Startup class for the KnowledgeFlow.
KnowledgeFlow() - Constructor for class weka.gui.beans.KnowledgeFlow
KnowledgeFlowApp - Class in weka.gui.beans
  Main GUI class for the KnowledgeFlow
KnowledgeFlowApp() - Constructor for class weka.gui.beans.KnowledgeFlowApp
  Creates a new `KnowledgeFlowApp` instance.
KOML - Class in weka.core.xml
  This class is a helper class for XML serialization using KOML .
KOML() - Constructor for class weka.core.xml.KOML
komlToBinary(String, String) - Static method in class weka.core.xml.SerialUIDChanger
  converts a KOML file into a binary one
KStar - Class in weka.classifiers.lazy
  K* is an instance-based classifier, that is the class of a test instance is based upon the class of those training instances similar to it, as determined by some similarity function.
KStar() - Constructor for class weka.classifiers.lazy.KStar
KStarCache - Class in weka.classifiers.lazy.kstar
  A class representing the caching system used to keep track of each attribute value and its corresponding scale factor or stop parameter.
KStarCache() - Constructor for class weka.classifiers.lazy.kstar.KStarCache
KStarCache.CacheTable - Class in weka.classifiers.lazy.kstar
  A custom hashtable class to support the caching system.
KStarCache.CacheTable(int, float) - Constructor for class weka.classifiers.lazy.kstar.KStarCache.CacheTable
  Constructs a new hashtable with a default capacity and load factor.
KStarCache.CacheTable() - Constructor for class weka.classifiers.lazy.kstar.KStarCache.CacheTable
  Constructs a new hashtable with a default capacity and load factor.
KStarCache.TableEntry - Class in weka.classifiers.lazy.kstar
  Hashtable collision list.
KStarCache.TableEntry(int, double, double, double, KStarCache.TableEntry) - Constructor for class weka.classifiers.lazy.kstar.KStarCache.TableEntry
  Constructor
KStarConstants - Interface in weka.classifiers.lazy.kstar
KStarNominalAttribute - Class in weka.classifiers.lazy.kstar
  A custom class which provides the environment for computing the transformation probability of a specified test instance nominal attribute to a specified train instance nominal attribute.
KStarNominalAttribute(Instance, Instance, int, Instances, int[][], KStarCache) - Constructor for class weka.classifiers.lazy.kstar.KStarNominalAttribute
  Constructor
KStarNumericAttribute - Class in weka.classifiers.lazy.kstar
  A custom class which provides the environment for computing the transformation probability of a specified test instance numeric attribute to a specified train instance numeric attribute.
KStarNumericAttribute(Instance, Instance, int, Instances, int[][], KStarCache) - Constructor for class weka.classifiers.lazy.kstar.KStarNumericAttribute
  Constructor
KStarWrapper - Class in weka.classifiers.lazy.kstar
KStarWrapper() - Constructor for class weka.classifiers.lazy.kstar.KStarWrapper
kthSmallestValue(Attribute, int) - Method in class weka.core.Instances
  Returns the kth-smallest attribute value of a numeric attribute.
kthSmallestValue(int, int) - Method in class weka.core.Instances
  Returns the kth-smallest attribute value of a numeric attribute.
kthSmallestValue(int[], int) - Static method in class weka.core.Utils
  Returns the kth-smallest value in the array.
kthSmallestValue(double[], int) - Static method in class weka.core.Utils
  Returns the kth-smallest value in the array
KValueTipText() - Method in class weka.classifiers.trees.RandomTree
  Returns the tip text for this property

## L

LabeledItemSet - Class in weka.associations
  Class for storing a set of items together with a class label.
LabeledItemSet(int, int) - Constructor for class weka.associations.LabeledItemSet
  Constructor
laplaceProb(int) - Method in class weka.classifiers.trees.j48.Distribution
  Returns relative frequency of class over all bags with Laplace correction.
laplaceProb(int, int) - Method in class weka.classifiers.trees.j48.Distribution
  Returns relative frequency of class for given bag.
lastElement() - Method in class weka.core.FastVector
  Returns the last element of the vector.
lastInstance() - Method in class weka.core.Instances
  Returns the last instance in the set.
launchNext(int, int) - Method in class weka.experiment.RemoteExperiment
  Launch a sub experiment on a remote host
layoutCompleted(LayoutCompleteEvent) - Method in class weka.gui.graphvisualizer.GraphVisualizer
  This method is an implementation for LayoutCompleteEventListener class.
layoutCompleted(LayoutCompleteEvent) - Method in interface weka.gui.graphvisualizer.LayoutCompleteEventListener
LayoutCompleteEvent - Class in weka.gui.graphvisualizer
  This is an event which is fired by a LayoutEngine once a LayoutEngine finishes laying out the graph, so that the Visualizer can repaint the screen to show the changes.
LayoutCompleteEvent(Object) - Constructor for class weka.gui.graphvisualizer.LayoutCompleteEvent
LayoutCompleteEventListener - Interface in weka.gui.graphvisualizer
  This interface should be implemented by any class which needs to receive LayoutCompleteEvents from the LayoutEngine.
LayoutEngine - Interface in weka.gui.graphvisualizer
  This interface class has been added to facilitate the addition of other layout engines to this package.
layoutGraph() - Method in class weka.gui.graphvisualizer.GraphVisualizer
  This method lays out the graph by calling the LayoutEngine's layoutGraph() method.
layoutGraph() - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine
  This method does a complete layout of the graph which includes removing cycles, assigning levels to nodes, reducing edge crossings and laying out the vertices horizontally for better visibility.
layoutGraph() - Method in interface weka.gui.graphvisualizer.LayoutEngine
  This method lays out the graph for better visualization
LBR - Class in weka.classifiers.lazy
  Lazy Bayesian Rules implement a lazy learning approach to lessening the attribute-independence assumption of naive Bayes.
LBR() - Constructor for class weka.classifiers.lazy.LBR
LBR.Indexes - Class in weka.classifiers.lazy
  Class for handling instances and the associated attributes.
LBR.Indexes(int, int, boolean, int) - Constructor for class weka.classifiers.lazy.LBR.Indexes
  constructor
LBR.Indexes(LBR.Indexes) - Constructor for class weka.classifiers.lazy.LBR.Indexes
  constructor
LearningRateResultProducer - Class in weka.experiment
  LearningRateResultProducer takes the results from a ResultProducer and submits the average to the result listener.
LearningRateResultProducer() - Constructor for class weka.experiment.LearningRateResultProducer
learningRateTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
leastExplainingColumn(PaceMatrix, IntVector, int, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Returns the index of the column that has the smallest (squared) response, when the column is moved to become the (ks-1)-th column.
LeastMedSq - Class in weka.classifiers.functions
  Implements a least median sqaured linear regression utilising the existing weka LinearRegression class to form predictions.
LeastMedSq() - Constructor for class weka.classifiers.functions.LeastMedSq
leaveOneOut(LBR.Indexes, int[][][], int[], boolean[]) - Method in class weka.classifiers.lazy.LBR
  Leave-one-out strategy.
leaveOneOutCV(BayesNet) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
  LeaveOneOutCV returns the accuracy calculated using Leave One Out cross validation.
leftNode() - Method in class weka.classifiers.trees.m5.RuleNode
  Get the left child of this node
leftSide(Instances) - Method in class weka.classifiers.trees.j48.BinC45Split
  Prints left side of condition..
leftSide(Instances) - Method in class weka.classifiers.trees.j48.C45Split
  Prints left side of condition..
leftSide(Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
  Prints left side of condition satisfied by instances.
leftSide(Instances) - Method in class weka.classifiers.trees.j48.NBTreeNoSplit
  Does nothing because no condition has to be satisfied.
leftSide(Instances) - Method in class weka.classifiers.trees.j48.NBTreeSplit
  Prints left side of condition..
leftSide(Instances) - Method in class weka.classifiers.trees.j48.NoSplit
  Does nothing because no condition has to be satisfied.
leftSide(Instances) - Method in class weka.classifiers.trees.lmt.ResidualSplit
  Returns name of splitting attribute (left side of condition).
legend() - Method in class weka.classifiers.trees.ADTree
  Returns the legend of the tree, describing how results are to be interpreted.
LegendPanel - Class in weka.gui.visualize
  This panel displays legends for a list of plots.
LegendPanel() - Constructor for class weka.gui.visualize.LegendPanel
  Constructor
leverageForRule(AprioriItemSet, AprioriItemSet, int, int) - Method in class weka.associations.AprioriItemSet
  Outputs the leverage for a rule.
liftForRule(AprioriItemSet, AprioriItemSet, int) - Method in class weka.associations.AprioriItemSet
  Outputs the lift for a rule.
likelihoodThresholdTipText() - Method in class weka.classifiers.meta.LogitBoost
  Returns the tip text for this property
LINE - Static variable in class weka.gui.visualize.VisualizePanelEvent
LinearRegression - Class in weka.classifiers.functions
  Class for using linear regression for prediction.
LinearRegression() - Constructor for class weka.classifiers.functions.LinearRegression
LinearRegression - Class in weka.core.matrix
  Class for performing (ridged) linear regression.
LinearRegression(Matrix, Matrix, double) - Constructor for class weka.core.matrix.LinearRegression
  Performs a (ridged) linear regression.
LinearRegression(Matrix, Matrix, double[], double) - Constructor for class weka.core.matrix.LinearRegression
  Performs a weighted (ridged) linear regression.
LinearUnit - Class in weka.classifiers.functions.neural
  This can be used by the neuralnode to perform all it's computations (as a Linear unit).
LinearUnit() - Constructor for class weka.classifiers.functions.neural.LinearUnit
listOptions() - Method in class weka.associations.Apriori
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.associations.PredictiveApriori
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.associations.Tertius
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.BestFirst
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.CfsSubsetEval
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.ChiSquaredAttributeEval
  Returns an enumeration describing the available options
listOptions() - Method in class weka.attributeSelection.ClassifierSubsetEval
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.ExhaustiveSearch
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.GainRatioAttributeEval
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.GeneticSearch
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.GreedyStepwise
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.InfoGainAttributeEval
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.OneRAttributeEval
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.PrincipalComponents
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.RaceSearch
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.RandomSearch
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.Ranker
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.RankSearch
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.ReliefFAttributeEval
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.SVMAttributeEval
  Returns an enumeration describing all the available options
listOptions() - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.WrapperSubsetEval
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.AODE
  Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.bayes.BayesNet
  Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.bayes.ComplementNaiveBayes
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.NaiveBayes
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.BayesNetGenerator
  Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator
  Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.bayes.net.estimate.BMAEstimator
  Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator
  Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.fixed.FromFile
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
  Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.bayes.net.search.global.HillClimber
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.global.K2
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.global.TabuSearch
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.global.TAN
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.local.HillClimber
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.local.K2
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
  Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.local.TabuSearch
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.local.TAN
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.SearchAlgorithm
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.BVDecompose
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.BVDecomposeSegCVSub
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.CheckClassifier
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.Classifier
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.LeastMedSq
  Returns an enumeration of all the available options..
listOptions() - Method in class weka.classifiers.functions.LinearRegression
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.Logistic
  Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.functions.MultilayerPerceptron
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.PaceRegression
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.RBFNetwork
  Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.functions.SimpleLogistic
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.SMO
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.SMOreg
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.VotedPerceptron
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.Winnow
  Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.IteratedSingleClassifierEnhancer
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.lazy.IBk
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.lazy.KStar
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.lazy.LWL
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.AdaBoostM1
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.AdditiveRegression
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.AttributeSelectedClassifier
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.Bagging
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.CostSensitiveClassifier
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.CVParameterSelection
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.Decorate
  Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.meta.FilteredClassifier
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.LogitBoost
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.MetaCost
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.MultiBoostAB
  Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.meta.MultiClassClassifier
  Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.meta.MultiScheme
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.OrdinalClassClassifier
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost
  Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.meta.RegressionByDiscretization
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.Stacking
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.ThresholdSelector
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.misc.VFI
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.MultipleClassifiersCombiner
  Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.RandomizableClassifier
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.RandomizableIteratedSingleClassifierEnhancer
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.RandomizableMultipleClassifiersCombiner
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.RandomizableSingleClassifierEnhancer
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.rules.ConjunctiveRule
  Returns an enumeration describing the available options Valid options are:
listOptions() - Method in class weka.classifiers.rules.DecisionTable
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.rules.JRip
  Returns an enumeration describing the available options Valid options are:
listOptions() - Method in class weka.classifiers.rules.NNge
  Returns an enumeration of all the available options..
listOptions() - Method in class weka.classifiers.rules.OneR
  Returns an enumeration describing the available options..
listOptions() - Method in class weka.classifiers.rules.PART
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.rules.Ridor
  Returns an enumeration describing the available options Valid options are:
listOptions() - Method in class weka.classifiers.SingleClassifierEnhancer
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.trees.ADTree
  Returns an enumeration describing the available options..
listOptions() - Method in class weka.classifiers.trees.J48
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.trees.LMT
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.trees.m5.M5Base
  Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.trees.M5P
  Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.trees.RandomForest
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.trees.RandomTree
  Lists the command-line options for this classifier.
listOptions() - Method in class weka.classifiers.trees.REPTree
  Lists the command-line options for this classifier.
listOptions() - Method in class weka.clusterers.Cobweb
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.clusterers.EM
  Returns an enumeration describing the available options..
listOptions() - Method in class weka.clusterers.FarthestFirst
  Returns an enumeration describing the available options..
listOptions() - Method in class weka.clusterers.MakeDensityBasedClusterer
  Returns an enumeration describing the available options..
listOptions() - Method in class weka.clusterers.SimpleKMeans
  Returns an enumeration describing the available options..
listOptions() - Method in class weka.core.converters.AbstractFileSaver
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.converters.C45Saver
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.converters.DatabaseLoader
  Lists the available options
listOptions() - Method in class weka.core.converters.DatabaseSaver
  Lists the available options
listOptions() - Method in interface weka.core.OptionHandler
  Returns an enumeration of all the available options..
listOptions() - Method in class weka.datagenerators.BIRCHCluster
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.datagenerators.RDG1
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.experiment.AveragingResultProducer
  Returns an enumeration describing the available options..
listOptions() - Method in class weka.experiment.ClassifierSplitEvaluator
  Returns an enumeration describing the available options..
listOptions() - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator
  Returns an enumeration describing the available options..
listOptions() - Method in class weka.experiment.CrossValidationResultProducer
  Returns an enumeration describing the available options..
listOptions() - Method in class weka.experiment.CSVResultListener
  Returns an enumeration describing the available options..
listOptions() - Method in class weka.experiment.DatabaseResultProducer
  Returns an enumeration describing the available options..
listOptions() - Method in class weka.experiment.Experiment
  Returns an enumeration describing the available options..
listOptions() - Method in class weka.experiment.InstanceQuery
  Returns an enumeration describing the available options
listOptions() - Method in class weka.experiment.LearningRateResultProducer
  Returns an enumeration describing the available options..
listOptions() - Method in class weka.experiment.PairedTTester
  Lists options understood by this object.
listOptions() - Method in class weka.experiment.RandomSplitResultProducer
  Returns an enumeration describing the available options..
listOptions() - Method in class weka.experiment.RegressionSplitEvaluator
  Returns an enumeration describing the available options..
listOptions() - Method in class weka.filters.supervised.attribute.AttributeSelection
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.supervised.attribute.ClassOrder
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.supervised.attribute.Discretize
  Gets an enumeration describing the available options.
listOptions() - Method in class weka.filters.supervised.attribute.NominalToBinary
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.supervised.instance.Resample
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.supervised.instance.SpreadSubsample
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds
  Gets an enumeration describing the available options..
listOptions() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.Add
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.AddCluster
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.AddExpression
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.AddNoise
  Returns an enumeration describing the available options
listOptions() - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat
  {@inheritDoc
listOptions() - Method in class weka.filters.unsupervised.attribute.ClusterMembership
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.Copy
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.Discretize
  Gets an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.FirstOrder
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.MakeIndicator
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.NominalToBinary
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.NumericTransform
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize
  Gets an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.RandomProjection
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.Remove
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.RemoveType
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.RemoveUseless
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.StringToNominal
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Returns an enumeration describing the available options
listOptions() - Method in class weka.filters.unsupervised.attribute.SwapValues
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.Normalize
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.Randomize
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.RemoveFolds
  Gets an enumeration describing the available options..
listOptions() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.RemovePercentage
  Gets an enumeration describing the available options..
listOptions() - Method in class weka.filters.unsupervised.instance.RemoveRange
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.RemoveWithValues
  Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.Resample
  Returns an enumeration describing the available options.
ListSelectorDialog - Class in weka.gui
  A dialog to present the user with a list of items, that the user can make a selection from, or cancel the selection.
ListSelectorDialog(Frame, JList) - Constructor for class weka.gui.ListSelectorDialog
  Create the list selection dialog.
Literal - Class in weka.associations.tertius
Literal(Predicate, int, int) - Constructor for class weka.associations.tertius.Literal
LiteralSet - Class in weka.associations.tertius
  Class representing a set of literals, being either the body or the head of a rule.
LiteralSet() - Constructor for class weka.associations.tertius.LiteralSet
  Constructor for a set that does not store its counter-instances.
LiteralSet(Instances) - Constructor for class weka.associations.tertius.LiteralSet
  Constructor initializing the set of counter-instances to all the instances.
LMT - Class in weka.classifiers.trees
  Class for "logistic model tree" classifier.
LMT() - Constructor for class weka.classifiers.trees.LMT
  Creates an instance of LMT with standard options
LMTNode - Class in weka.classifiers.trees.lmt
  Class for logistic model tree structure.
LMTNode(ModelSelection, int, boolean, boolean, int) - Constructor for class weka.classifiers.trees.lmt.LMTNode
  Constructor for logistic model tree node.
lnFactorial(int) - Method in class weka.classifiers.bayes.NaiveBayesMultinomial
  Fast computation of ln(n!) for non-negative ints negative ints are passed on to the general gamma-function based version in weka.core.SpecialFunctions if the current n value is higher than any previous one, the cache is extended and filled to cover it the common case is reduced to a simple array lookup
lnFactorial(double) - Static method in class weka.core.SpecialFunctions
  Returns natural logarithm of factorial using gamma function.
lnGamma(double) - Static method in class weka.core.Statistics
  Returns natural logarithm of gamma function.
LNormTipText() - Method in class weka.filters.unsupervised.instance.Normalize
  Returns the tip text for this property
lnsrch(double[], double[], double[], double, boolean[], double[][], Optimization.DynamicIntArray) - Method in class weka.core.Optimization
  Find a new point x in the direction p from a point xold at which the value of the function has decreased sufficiently, the positive definiteness of B matrix (approximation of the inverse of the Hessian) is preserved and no bound constraints are violated.
load(InputStream) - Method in class weka.core.ProtectedProperties
  Overrides a method to prevent the properties from being modified.
Loader - Interface in weka.core.converters
  Interface to something that can load Instances from an input source in some format.
Loader - Class in weka.gui.beans
  Loads data sets using weka.core.converter classes
Loader() - Constructor for class weka.gui.beans.Loader
Loader - Class in weka.gui
  This class is for loading resources from a JAR archive.
Loader(String) - Constructor for class weka.gui.Loader
  initializes the object
LoaderBeanInfo - Class in weka.gui.beans
  Bean info class for the loader bean
LoaderBeanInfo() - Constructor for class weka.gui.beans.LoaderBeanInfo
LoaderCustomizer - Class in weka.gui.beans
  GUI Customizer for the loader bean
LoaderCustomizer() - Constructor for class weka.gui.beans.LoaderCustomizer
loadFile(String) - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  loads the specified file
loadFile() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  loads the specified file into the table
loadIcons(String, String) - Method in class weka.gui.beans.BeanVisual
  Loads static and animated versions of a beans icons.
localDistributionForInstance(Instance, LBR.Indexes) - Method in class weka.classifiers.lazy.LBR
  Calculates the class membership probabilities.
locallyPredictiveTipText() - Method in class weka.attributeSelection.CfsSubsetEval
  Returns the tip text for this property
localNaiveBayes(LBR.Indexes) - Method in class weka.classifiers.lazy.LBR
  Class for building and using a simple Naive Bayes classifier.
LocalScoreSearchAlgorithm - Class in weka.classifiers.bayes.net.search.local
  The ScoreBasedSearchAlgorithm class supports Bayes net structure search algorithms that are based on maximizing scores (as opposed to for example conditional independence based search algorithms).
LocalScoreSearchAlgorithm() - Constructor for class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
LocalScoreSearchAlgorithm(BayesNet, Instances) - Constructor for class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
locateIndex(int) - Method in class weka.core.SparseInstance
  Locates the greatest index that is not greater than the given index.
LOG2 - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
log2 - Static variable in class weka.core.Utils
  The natural logarithm of 2.
log2(double) - Static method in class weka.core.Utils
  Returns the logarithm of a for base 2.
log2Binomial(double, double) - Static method in class weka.core.SpecialFunctions
  Returns base 2 logarithm of binomial coefficient using gamma function.
log2Multinomial(double, double[]) - Static method in class weka.core.SpecialFunctions
  Returns base 2 logarithm of multinomial using gamma function.
log2MultipleHypergeometric(double[][]) - Static method in class weka.core.ContingencyTables
  Returns negative base 2 logarithm of multiple hypergeometric probability for a contingency table.
logbinomialCoefficient(int, int) - Static method in class weka.associations.PriorEstimation
  Method that calculates the base 2 logarithm of a binomial coefficient
logDensityForInstance(Instance) - Method in class weka.clusterers.DensityBasedClusterer
  Computes the density for a given instance.
logDensityPerClusterForInstance(Instance) - Method in class weka.clusterers.DensityBasedClusterer
  Computes the log of the conditional density (per cluster) for a given instance.
logDensityPerClusterForInstance(Instance) - Method in class weka.clusterers.EM
  Computes the log of the conditional density (per cluster) for a given instance.
logDensityPerClusterForInstance(Instance) - Method in class weka.clusterers.MakeDensityBasedClusterer
  Computes the log of the conditional density (per cluster) for a given instance.
logFunc(double) - Method in class weka.classifiers.trees.j48.EntropyBasedSplitCrit
  Help method for computing entropy.
Logger - Interface in weka.gui
  Interface for objects that display log (permanent historical) and status (transient) messages.
Logistic - Class in weka.classifiers.functions
  Second implementation for building and using a multinomial logistic regression model with a ridge estimator.
Logistic() - Constructor for class weka.classifiers.functions.Logistic
LogisticBase - Class in weka.classifiers.trees.lmt
  Base/helper class for building logistic regression models with the LogitBoost algorithm.
LogisticBase() - Constructor for class weka.classifiers.trees.lmt.LogisticBase
  Constructor that creates LogisticBase object with standard options.
LogisticBase(int, boolean, boolean) - Constructor for class weka.classifiers.trees.lmt.LogisticBase
  Constructor to create LogisticBase object.
LogitBoost - Class in weka.classifiers.meta
  Class for performing additive logistic regression..
LogitBoost() - Constructor for class weka.classifiers.meta.LogitBoost
  Constructor.
logJointDensitiesForInstance(Instance) - Method in class weka.clusterers.DensityBasedClusterer
  Returns the logs of the joint densities for a given instance.
logMessage(String) - Method in interface weka.gui.Logger
  Sends the supplied message to the log area.
logMessage(String) - Method in class weka.gui.LogPanel
  Sends the supplied message to the log area.
logMessage(String) - Method in class weka.gui.SysErrLog
  Sends the supplied message to the log area.
LogPanel - Class in weka.gui
  This panel allows log and status messages to be posted.
LogPanel() - Constructor for class weka.gui.LogPanel
  Creates the log panel with no task monitor and the log always visible.
LogPanel(WekaTaskMonitor) - Constructor for class weka.gui.LogPanel
  Creates the log panel with a task monitor, where the log is hidden.
LogPanel(WekaTaskMonitor, boolean) - Constructor for class weka.gui.LogPanel
  Creates the log panel, possibly with task monitor, where the log is optionally hidden.
logPSI - Static variable in class weka.classifiers.functions.pace.Maths
  The constant - log( sqrt(2 pi) )
logs2probs(double[]) - Static method in class weka.core.Utils
  Converts an array containing the natural logarithms of probabilities stored in a vector back into probabilities.
logScore(int, int) - Method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes
  Gets the log score contribution of this distribution
logScore(int) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
  logScore returns the log of the quality of a network (e.g.
logScore(int, int) - Method in interface weka.classifiers.bayes.net.search.local.Scoreable
  Returns log-score
LONG - Static variable in class weka.core.converters.DatabaseLoader
LONG - Static variable in class weka.experiment.DatabaseUtils
  Type mapping for LONG used for reading experiment results
LookAndFeel - Class in weka.gui
  A little helper class for setting the Look and Feel of the user interface.
LookAndFeel() - Constructor for class weka.gui.LookAndFeel
lookupCacheSizeTipText() - Method in class weka.attributeSelection.BestFirst
  Returns the tip text for this property
lowerBoundMinSupportTipText() - Method in class weka.associations.Apriori
  Returns the tip text for this property
lowerCaseTokensTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Returns the tip text for this property.
lowerNumericBoundIsOpen() - Method in class weka.core.Attribute
  Returns whether the lower numeric bound of the attribute is open.
lowerOrderTermsTipText() - Method in class weka.classifiers.functions.SMO
  Returns the tip text for this property
lowerOrderTermsTipText() - Method in class weka.classifiers.functions.SMOreg
  Returns the tip text for this property
lowerSizeTipText() - Method in class weka.experiment.LearningRateResultProducer
  Returns the tip text for this property
lsqr(PaceMatrix, IntVector, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
  QR transformation for a least squares problem A x = b
lsqrSelection(PaceMatrix, IntVector, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
  QR transformation for a least squares problem A x = b
lu() - Method in class weka.core.matrix.Matrix
  LU Decomposition
LUDecomposition - Class in weka.core.matrix
  LU Decomposition.
LUDecomposition() - Method in class weka.core.Matrix
  Deprecated. Performs a LUDecomposition on the matrix.
LUDecomposition(Matrix) - Constructor for class weka.core.matrix.LUDecomposition
  LU Decomposition
LWL - Class in weka.classifiers.lazy
  Locally-weighted learning.
LWL() - Constructor for class weka.classifiers.lazy.LWL
  Constructor.

## M

M5Base - Class in weka.classifiers.trees.m5
  M5Base.
M5Base() - Constructor for class weka.classifiers.trees.m5.M5Base
  Constructor
M5P - Class in weka.classifiers.trees
  M5P.
M5P() - Constructor for class weka.classifiers.trees.M5P
  Creates a new `M5P` instance.
M5Rules - Class in weka.classifiers.rules
  Generates a decision list for regression problems using separate-and-conquer.
M5Rules() - Constructor for class weka.classifiers.rules.M5Rules
m_ADNodes - Variable in class weka.classifiers.bayes.net.VaryNode
  list of ADNode children
m_alpha - Variable in class weka.classifiers.trees.lmt.LMTNode
  Alpha-value (for pruning) at the node
m_AttIndexes - Variable in class weka.classifiers.lazy.LBR.Indexes
  the array attribute indexes
M_AVERAGE - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
m_ClassIndex - Variable in class weka.classifiers.lazy.LBR.Indexes
  the Class Index for the data set
m_col - Variable in class weka.gui.treevisualizer.NamedColor
  The actual color object
m_cols - Variable in class weka.gui.treevisualizer.Colors
  The array with all the colors input
m_customColour - Variable in class weka.gui.visualize.PlotData2D
M_DELETE - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
  Missing value handling mode
m_displayAllPoints - Variable in class weka.gui.visualize.PlotData2D
  Display all points (ie.
m_Distributions - Variable in class weka.classifiers.bayes.BayesNet
  The attribute estimators containing CPTs.
m_experimentFinished - Variable in class weka.experiment.RemoteExperimentEvent
  True if a remote experiment has finished
m_indexVal - Variable in class weka.gui.visualize.AttributePanelEvent
  The index for the new attribute
m_iNode - Variable in class weka.classifiers.bayes.net.VaryNode
  index of the node varied
m_Instances - Variable in class weka.classifiers.bayes.BayesNet
  The dataset header for the purposes of printing out a semi-intelligible model
m_Instances - Variable in class weka.classifiers.bayes.net.ADNode
  list of Instance children (either m_Instances or m_VaryNodes is instantiated)
m_InstIndexes - Variable in class weka.classifiers.lazy.LBR.Indexes
  the array instance indexes
m_logMessage - Variable in class weka.experiment.RemoteExperimentEvent
  A log type message
M_MAXDIFF - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
m_messageString - Variable in class weka.experiment.RemoteExperimentEvent
  The message
m_name - Variable in class weka.gui.treevisualizer.NamedColor
  The name of the color
m_nCount - Variable in class weka.classifiers.bayes.net.ADNode
  count
m_nMCV - Variable in class weka.classifiers.bayes.net.VaryNode
  most common value
M_NORMAL - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
m_nStartNode - Variable in class weka.classifiers.bayes.net.ADNode
  first node in VaryNode array
m_NumAttsSet - Variable in class weka.classifiers.lazy.LBR.Indexes
  the number of attributes "in use" or set to a the original value (true or false)
m_numIncorrectModel - Variable in class weka.classifiers.trees.lmt.LMTNode
  Weighted number of training examples currently misclassified by the logistic model at the node
m_numIncorrectTree - Variable in class weka.classifiers.trees.lmt.LMTNode
  Weighted number of training examples currently misclassified by the subtree rooted at the node
m_NumInstsSet - Variable in class weka.classifiers.lazy.LBR.Indexes
  the number of instances "in use" or set to a the original value (true or false)
m_numParameters - Variable in class weka.classifiers.trees.m5.RuleNode
  the number of paramters in the chosen model for this node---either the subtree model or the linear model.
m_NumSeqAttsSet - Variable in class weka.classifiers.lazy.LBR.Indexes
  the number of sequential attributes "in use" or set to a the original value (true or false)
m_NumSeqInstsSet - Variable in class weka.classifiers.lazy.LBR.Indexes
  the number of sequential instances "in use" or set to a the original value (true or false)
m_SequentialAttIndexes - Variable in class weka.classifiers.lazy.LBR.Indexes
  an array of attribute indexes that are set to either true or false
m_SequentialInstIndexes - Variable in class weka.classifiers.lazy.LBR.Indexes
  the array of instance indexes that are set to a either true or false
m_statusMessage - Variable in class weka.experiment.RemoteExperimentEvent
  A status type message
m_useCustomColour - Variable in class weka.gui.visualize.PlotData2D
  Custom colour for this plot
m_VaryNodes - Variable in class weka.classifiers.bayes.net.ADNode
  list of VaryNode children
m_xChange - Variable in class weka.gui.visualize.AttributePanelEvent
  True if the x selection changed
m_yChange - Variable in class weka.gui.visualize.AttributePanelEvent
  True if the y selection changed
MahalanobisEstimator - Class in weka.estimators
  Simple probability estimator that places a single normal distribution over the observed values.
MahalanobisEstimator(Matrix, double, double) - Constructor for class weka.estimators.MahalanobisEstimator
  Constructor
main(String[]) - Static method in class weka.associations.Apriori
  Main method for testing this class.
main(String[]) - Static method in class weka.associations.PredictiveApriori
  Main method for testing this class.
main(String[]) - Static method in class weka.associations.Tertius
  Main method for testing this class.
main(String[]) - Static method in class weka.attributeSelection.AttributeSelection
  Main method for testing this class.
main(String[]) - Static method in class weka.attributeSelection.CfsSubsetEval
  Main method for testing this class.
main(String[]) - Static method in class weka.attributeSelection.ChiSquaredAttributeEval
  Main method for testing this class.
main(String[]) - Static method in class weka.attributeSelection.ClassifierSubsetEval
  Main method for testing this class.
main(String[]) - Static method in class weka.attributeSelection.ConsistencySubsetEval
  Main method for testing this class.
main(String[]) - Static method in class weka.attributeSelection.GainRatioAttributeEval
  Main method for testing this class.
main(String[]) - Static method in class weka.attributeSelection.InfoGainAttributeEval
  Main method for testing this class.
main(String[]) - Static method in class weka.attributeSelection.OneRAttributeEval
  Main method for testing this class.
main(String[]) - Static method in class weka.attributeSelection.PrincipalComponents
  Main method for testing this class
main(String[]) - Static method in class weka.attributeSelection.ReliefFAttributeEval
  Main method for testing this class.
main(String[]) - Static method in class weka.attributeSelection.SVMAttributeEval
  Main method for testing this class.
main(String[]) - Static method in class weka.attributeSelection.SymmetricalUncertAttributeEval
  Main method for testing this class.
main(String[]) - Static method in class weka.attributeSelection.WrapperSubsetEval
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.bayes.AODE
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.bayes.BayesNet
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.bayes.ComplementNaiveBayes
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.bayes.NaiveBayes
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.bayes.NaiveBayesMultinomial
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.bayes.NaiveBayesSimple
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.bayes.NaiveBayesUpdateable
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.bayes.net.ADNode
main(String[]) - Static method in class weka.classifiers.bayes.net.BayesNetGenerator
main(String[]) - Static method in class weka.classifiers.bayes.net.BIFReader
main(String[]) - Static method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorFullBayes
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm
main(String[]) - Static method in class weka.classifiers.BVDecompose
  Test method for this class
main(String[]) - Static method in class weka.classifiers.BVDecomposeSegCVSub
  Test method for this class
main(String[]) - Static method in class weka.classifiers.CheckClassifier
  Test method for this class
main(String[]) - Static method in class weka.classifiers.evaluation.CostCurve
  Tests the CostCurve generation from the command line.
main(String[]) - Static method in class weka.classifiers.Evaluation
  A test method for this class.
main(String[]) - Static method in class weka.classifiers.evaluation.MarginCurve
  Tests the MarginCurve generation from the command line.
main(String[]) - Static method in class weka.classifiers.evaluation.ThresholdCurve
  Tests the ThresholdCurve generation from the command line.
main(String[]) - Static method in class weka.classifiers.functions.LeastMedSq
  generate a Linear regression predictor for testing
main(String[]) - Static method in class weka.classifiers.functions.LinearRegression
  Generates a linear regression function predictor.
main(String[]) - Static method in class weka.classifiers.functions.Logistic
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.functions.MultilayerPerceptron
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.functions.pace.ChisqMixture
  Method to test this class
main(String[]) - Static method in class weka.classifiers.functions.pace.DiscreteFunction
main(String[]) - Static method in class weka.classifiers.functions.pace.DoubleVector
main(String[]) - Static method in class weka.classifiers.functions.pace.IntVector
  Tests the IntVector class
main(String[]) - Static method in class weka.classifiers.functions.pace.NormalMixture
  Method to test this class
main(String[]) - Static method in class weka.classifiers.functions.pace.PaceMatrix
main(String[]) - Static method in class weka.classifiers.functions.PaceRegression
  Generates a linear regression function predictor.
main(String[]) - Static method in class weka.classifiers.functions.RBFNetwork
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.functions.SimpleLinearRegression
  Main method for testing this class
main(String[]) - Static method in class weka.classifiers.functions.SimpleLogistic
  Main method for testing this class
main(String[]) - Static method in class weka.classifiers.functions.SMO
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.functions.SMOreg
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.functions.VotedPerceptron
  Main method.
main(String[]) - Static method in class weka.classifiers.functions.Winnow
  Main method.
main(String[]) - Static method in class weka.classifiers.lazy.IB1
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.lazy.IBk
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.lazy.KStar
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.lazy.LBR
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.lazy.LWL
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.AdaBoostM1
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.AdditiveRegression
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.AttributeSelectedClassifier
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.Bagging
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.ClassificationViaRegression
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.CostSensitiveClassifier
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.CVParameterSelection
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.Decorate
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.FilteredClassifier
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.Grading
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.LogitBoost
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.MetaCost
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.MultiBoostAB
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.MultiClassClassifier
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.MultiScheme
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.OrdinalClassClassifier
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.RacedIncrementalLogitBoost
  Main method for this class.
main(String[]) - Static method in class weka.classifiers.meta.RandomCommittee
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.RegressionByDiscretization
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.Stacking
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.StackingC
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.ThresholdSelector
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.Vote
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.misc.HyperPipes
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.misc.VFI
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.rules.ConjunctiveRule
  Main method.
main(String[]) - Static method in class weka.classifiers.rules.DecisionTable
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.rules.JRip
  Main method.
main(String[]) - Static method in class weka.classifiers.rules.M5Rules
  Main method by which this class can be tested
main(String[]) - Static method in class weka.classifiers.rules.NNge
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.rules.OneR
  Main method for testing this class
main(String[]) - Static method in class weka.classifiers.rules.PART
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.rules.Prism
  Main method for testing this class
main(String[]) - Static method in class weka.classifiers.rules.Ridor
  Main method.
main(String[]) - Static method in class weka.classifiers.rules.ZeroR
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.trees.ADTree
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.trees.DecisionStump
  Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.trees.Id3
  Main method.
main(String[]) - Static method in class weka.classifiers.trees.J48
  Main method for testing this class
main(String[]) - Static method in class weka.classifiers.trees.LMT
  Main method for testing this class
main(String[]) - Static method in class weka.classifiers.trees.M5P
  Main method by which this class can be tested
main(String[]) - Static method in class weka.classifiers.trees.NBTree
  Main method for testing this class
main(String[]) - Static method in class weka.classifiers.trees.RandomForest
  Main method for this class.
main(String[]) - Static method in class weka.classifiers.trees.RandomTree
  Main method for this class.
main(String[]) - Static method in class weka.classifiers.trees.REPTree
  Main method for this class.
main(String[]) - Static method in class weka.classifiers.trees.UserClassifier
  Main method for testing this class.
main(String[]) - Static method in class weka.clusterers.ClusterEvaluation
  Main method for testing this class.
main(String[]) - Static method in class weka.clusterers.Cobweb
main(String[]) - Static method in class weka.clusterers.EM
  Main method for testing this class.
main(String[]) - Static method in class weka.clusterers.FarthestFirst
  Main method for testing this class.
main(String[]) - Static method in class weka.clusterers.MakeDensityBasedClusterer
  Main method for testing this class.
main(String[]) - Static method in class weka.clusterers.SimpleKMeans
  Main method for testing this class.
main(String[]) - Static method in class weka.core.Attribute
  Simple main method for testing this class.
main(String[]) - Static method in class weka.core.BinarySparseInstance
  Main method for testing this class.
main(String[]) - Static method in class weka.core.CheckOptionHandler
  Main method for using the CheckOptionHandler.
main(String[]) - Static method in class weka.core.ContingencyTables
  Main method for testing this class.
main(String[]) - Static method in class weka.core.converters.ArffLoader
  Main method.
main(String[]) - Static method in class weka.core.converters.ArffSaver
  Main method.
main(String[]) - Static method in class weka.core.converters.C45Loader
  Main method for testing this class.
main(String[]) - Static method in class weka.core.converters.C45Saver
  Main method.
main(String[]) - Static method in class weka.core.converters.CSVLoader
  Main method.
main(String[]) - Static method in class weka.core.converters.CSVSaver
  Main method.
main(String[]) - Static method in class weka.core.converters.DatabaseLoader
  Main method.
main(String[]) - Static method in class weka.core.converters.DatabaseSaver
  Main method.
main(String[]) - Static method in class weka.core.converters.SerializedInstancesLoader
  Main method.
main(String[]) - Static method in class weka.core.converters.SerializedInstancesSaver
  Main method.
main(String[]) - Static method in class weka.core.Instance
  Main method for testing this class.
main(String[]) - Static method in class weka.core.InstanceComparator
  for testing only.
main(String[]) - Static method in class weka.core.Instances
  Main method for this class.
main(String[]) - Static method in class weka.core.Matrix
  Deprecated. Main method for testing this class.
main(String[]) - Static method in class weka.core.matrix.Matrix
  Main method for testing this class.
main(String[]) - Static method in class weka.core.Queue
  Main method for testing this class.
main(String[]) - Static method in class weka.core.RandomVariates
  Main method for testing this class.
main(String[]) - Static method in class weka.core.Range
  Main method for testing this class.
main(String[]) - Static method in class weka.core.RTSI
  for testing only
main(String[]) - Static method in class weka.core.SingleIndex
  Main method for testing this class.
main(String[]) - Static method in class weka.core.SparseInstance
  Main method for testing this class.
main(String[]) - Static method in class weka.core.SpecialFunctions
  Main method for testing this class.
main(String[]) - Static method in class weka.core.Statistics
  Main method for testing this class.
main(String[]) - Static method in class weka.core.SystemInfo
  for printing the system info to stdout.
main(String[]) - Static method in class weka.core.Utils
  Main method for testing this class.
main(String[]) - Static method in class weka.core.Version
  only for testing
main(String[]) - Static method in class weka.core.xml.SerialUIDChanger
  exchanges an old UID for a new one.
main(String[]) - Static method in class weka.core.xml.XMLDocument
  for testing only.
main(String[]) - Static method in class weka.core.xml.XMLOptions
  for testing only.
main(String[]) - Static method in class weka.core.xml.XMLSerialization
  for testing only.
main(String[]) - Static method in class weka.datagenerators.BIRCHCluster
  Main method for testing this class.
main(String[]) - Static method in class weka.datagenerators.RDG1
  Main method for testing this class.
main(String[]) - Static method in class weka.estimators.DDConditionalEstimator
  Main method for testing this class.
main(String[]) - Static method in class weka.estimators.DiscreteEstimator
  Main method for testing this class.
main(String[]) - Static method in class weka.estimators.DKConditionalEstimator
  Main method for testing this class.
main(String[]) - Static method in class weka.estimators.DNConditionalEstimator
  Main method for testing this class.
main(String[]) - Static method in class weka.estimators.KDConditionalEstimator
  Main method for testing this class.
main(String[]) - Static method in class weka.estimators.KernelEstimator
  Main method for testing this class.
main(String[]) - Static method in class weka.estimators.KKConditionalEstimator
  Main method for testing this class.
main(String[]) - Static method in class weka.estimators.MahalanobisEstimator
  Main method for testing this class.
main(String[]) - Static method in class weka.estimators.NDConditionalEstimator
  Main method for testing this class.
main(String[]) - Static method in class weka.estimators.NNConditionalEstimator
  Main method for testing this class.
main(String[]) - Static method in class weka.estimators.NormalEstimator
  Main method for testing this class.
main(String[]) - Static method in class weka.estimators.PoissonEstimator
  Main method for testing this class.
main(String[]) - Static method in class weka.experiment.CrossValidationResultProducer
main(String[]) - Static method in class weka.experiment.Experiment
  Configures/Runs the Experiment from the command line.
main(String[]) - Static method in class weka.experiment.InstanceQuery
  Test the class from the command line.
main(String[]) - Static method in class weka.experiment.OutputZipper
  Main method for testing this class
main(String[]) - Static method in class weka.experiment.PairedCorrectedTTester
  Test the class from the command line.
main(String[]) - Static method in class weka.experiment.PairedStats
  Tests the paired stats object from the command line.
main(String[]) - Static method in class weka.experiment.PairedTTester
  Test the class from the command line.
main(String[]) - Static method in class weka.experiment.RemoteEngine
  Main method.
main(String[]) - Static method in class weka.experiment.RemoteExperiment
  Configures/Runs the Experiment from the command line.
main(String[]) - Static method in class weka.experiment.Stats
  Tests the paired stats object from the command line.
main(String[]) - Static method in class weka.experiment.xml.XMLExperiment
  for testing only.
main(String[]) - Static method in class weka.filters.AllFilter
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.Filter
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.NullFilter
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.supervised.attribute.AttributeSelection
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.supervised.attribute.ClassOrder
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.supervised.attribute.Discretize
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.supervised.attribute.NominalToBinary
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.supervised.instance.Resample
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.supervised.instance.SpreadSubsample
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.supervised.instance.StratifiedRemoveFolds
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.Add
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.AddCluster
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.AddExpression
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.AddNoise
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.ChangeDateFormat
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.ClusterMembership
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.Copy
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.Discretize
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.FirstOrder
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.MakeIndicator
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.MergeTwoValues
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.NominalToBinary
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.Normalize
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.NumericToBinary
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.NumericTransform
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.Obfuscate
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.PKIDiscretize
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.RandomProjection
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.Remove
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.RemoveType
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.RemoveUseless
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.ReplaceMissingValues
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.Standardize
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.StringToNominal
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.StringToWordVector
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.SwapValues
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.TimeSeriesDelta
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.TimeSeriesTranslate
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.NonSparseToSparse
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.Normalize
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.Randomize
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveFolds
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveMisclassified
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.RemovePercentage
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveRange
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveWithValues
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.Resample
  Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.SparseToNonSparse
  Main method for testing this class.
main(String[]) - Static method in class weka.gui.arffviewer.ArffViewer
  shows the frame and it tries to load all the arff files that were provided as arguments.
main(String[]) - Static method in class weka.gui.AttributeListPanel
  Tests the attribute list panel from the command line.
main(String[]) - Static method in class weka.gui.AttributeSelectionPanel
  Tests the attribute selection panel from the command line.
main(String[]) - Static method in class weka.gui.AttributeSummaryPanel
  Tests out the attribute summary panel from the command line.
main(String[]) - Static method in class weka.gui.AttributeVisualizationPanel
  Main method to test this class from command line
main(String[]) - Static method in class weka.gui.beans.AttributeSummarizer
main(String[]) - Static method in class weka.gui.beans.DataVisualizer
main(String[]) - Static method in class weka.gui.beans.KnowledgeFlow
  Shows the splash screen, launches the application and then disposes the splash screen.
main(String[]) - Static method in class weka.gui.beans.KnowledgeFlowApp
  Main method.
main(String[]) - Static method in class weka.gui.beans.Loader
main(String[]) - Static method in class weka.gui.beans.ModelPerformanceChart
main(String[]) - Static method in class weka.gui.beans.Saver
  The main method for testing
main(String[]) - Static method in class weka.gui.beans.ScatterPlotMatrix
main(String[]) - Static method in class weka.gui.beans.StripChart
  Tests out the StripChart from the command line
main(String[]) - Static method in class weka.gui.beans.TextViewer
main(String[]) - Static method in class weka.gui.boundaryvisualizer.BoundaryPanel
  Main method for testing this class
main(String[]) - Static method in class weka.gui.boundaryvisualizer.BoundaryPanelDistributed
  Main method for testing this class
main(String[]) - Static method in class weka.gui.boundaryvisualizer.BoundaryVisualizer
  Main method for testing this class
main(String[]) - Static method in class weka.gui.DatabaseConnectionDialog
main(String[]) - Static method in class weka.gui.experiment.AlgorithmListPanel
  Tests out the algorithm list panel from the command line.
main(String[]) - Static method in class weka.gui.experiment.DatasetListPanel
  Tests out the dataset list panel from the command line.
main(String[]) - Static method in class weka.gui.experiment.DistributeExperimentPanel
  Tests out the panel from the command line.
main(String[]) - Static method in class weka.gui.experiment.Experimenter
  Tests out the experiment environment.
main(String[]) - Static method in class weka.gui.experiment.GeneratorPropertyIteratorPanel
  Tests out the panel from the command line.
main(String[]) - Static method in class weka.gui.experiment.HostListPanel
  Tests out the host list panel from the command line.
main(String[]) - Static method in class weka.gui.experiment.OutputFormatDialog
  for testing only
main(String[]) - Static method in class weka.gui.experiment.ResultsPanel
  Tests out the results panel from the command line.
main(String[]) - Static method in class weka.gui.experiment.RunNumberPanel
  Tests out the panel from the command line.
main(String[]) - Static method in class weka.gui.experiment.RunPanel
  Tests out the run panel from the command line.
main(String[]) - Static method in class weka.gui.experiment.SetupPanel
  Tests out the experiment setup from the command line.
main(String[]) - Static method in class weka.gui.experiment.SimpleSetupPanel
  Tests out the experiment setup from the command line.
main(String[]) - Static method in class weka.gui.explorer.AssociationsPanel
  Tests out the Associator panel from the command line.
main(String[]) - Static method in class weka.gui.explorer.AttributeSelectionPanel
  Tests out the attribute selection panel from the command line.
main(String[]) - Static method in class weka.gui.explorer.ClassifierPanel
  Tests out the classifier panel from the command line.
main(String[]) - Static method in class weka.gui.explorer.ClustererPanel
  Tests out the clusterer panel from the command line.
main(String[]) - Static method in class weka.gui.explorer.Explorer
  Tests out the explorer environment.
main(String[]) - Static method in class weka.gui.explorer.PreprocessPanel
  Tests out the instance-preprocessing panel from the command line.
main(String[]) - Static method in class weka.gui.GenericArrayEditor
  Tests out the array editor from the command line.
main(String[]) - Static method in class weka.gui.GenericObjectEditor
  Tests out the Object editor from the command line.
main(String[]) - Static method in class weka.gui.GenericPropertiesCreator
  for generating props file: no parameter: see default constructor 1 parameter (i.e., filename): see default constructor + setOutputFilename(String) 2 parameters (i.e, filenames): see constructor with String argument + setOutputFilename(String)
main(String[]) - Static method in class weka.gui.graphvisualizer.GraphVisualizer
  Main method to load a text file with the description of a graph from the command line
main(String[]) - Static method in class weka.gui.GUIChooser
  Tests out the GUIChooser environment.
main(String[]) - Static method in class weka.gui.HierarchyPropertyParser
  Tests out the parser.
main(String[]) - Static method in class weka.gui.InstancesSummaryPanel
  Tests out the instance summary panel from the command line.
main(String[]) - Static method in class weka.gui.ListSelectorDialog
  Tests out the list selector from the command line.
main(String[]) - Static method in class weka.gui.LogPanel
  Tests out the log panel from the command line.
main(String[]) - Static method in class weka.gui.LookAndFeel
  prints all the available LnFs to stdout
main(String[]) - Static method in class weka.gui.PropertySelectorDialog
  Tests out the property selector from the command line.
main(String[]) - Static method in class weka.gui.ResultHistoryPanel
  Tests out the result history from the command line.
main(String[]) - Static method in class weka.gui.SaveBuffer
  Main method for testing this class
main(String[]) - Static method in class weka.gui.SelectedTagEditor
  Tests out the selectedtag editor from the command line.
main(String[]) - Static method in class weka.gui.SimpleCLI
  Method to start up the simple cli
main(String[]) - Static method in class weka.gui.treevisualizer.TreeVisualizer
  Main method for testing this class.
main(String[]) - Static method in class weka.gui.visualize.AttributePanel
  Main method for testing this class.
main(String[]) - Static method in class weka.gui.visualize.ClassPanel
  Main method for testing this class.
main(String[]) - Static method in class weka.gui.visualize.JPEGWriter
  for testing only
main(String[]) - Static method in class weka.gui.visualize.LegendPanel
  Main method for testing this class
main(String[]) - Static method in class weka.gui.visualize.MatrixPanel
  Main method for testing this class
main(String[]) - Static method in class weka.gui.visualize.Plot2D
  Main method for testing this class
main(String[]) - Static method in class weka.gui.visualize.PostscriptWriter
  for testing only
main(String[]) - Static method in class weka.gui.visualize.VisualizePanel
  Main method for testing this class
main(String[]) - Static method in class weka.gui.WekaTaskMonitor
  Main method for testing this class
MAJOR - Static variable in class weka.core.Version
  the major version
majorityClassTipText() - Method in class weka.classifiers.rules.Ridor
  Returns the tip text for this property
makeADTree(int, FastVector, Instances) - Static method in class weka.classifiers.bayes.net.ADNode
  create sub tree
makeADTree(Instances) - Static method in class weka.classifiers.bayes.net.ADNode
  create AD tree from set of instances
makeBinaryTipText() - Method in class weka.filters.supervised.attribute.Discretize
  Returns the tip text for this property
makeBinaryTipText() - Method in class weka.filters.unsupervised.attribute.Discretize
  Returns the tip text for this property
makeCopies(Associator, int) - Static method in class weka.associations.Associator
  Creates copies of the current associator.
makeCopies(ASEvaluation, int) - Static method in class weka.attributeSelection.ASEvaluation
  Creates copies of the current evaluator.
makeCopies(Classifier, int) - Static method in class weka.classifiers.Classifier
  Creates a given number of deep copies of the given classifier using serialization.
makeCopies(Clusterer, int) - Static method in class weka.clusterers.Clusterer
  Creates copies of the current clusterer.
makeCopies(DensityBasedClusterer, int) - Static method in class weka.clusterers.DensityBasedClusterer
  Creates copies of the current clusterer.
makeCopy(Classifier) - Static method in class weka.classifiers.Classifier
  Creates a deep copy of the given classifier using serialization.
makeCopy(Object) - Method in class weka.gui.GenericObjectEditor
  Makes a copy of an object using serialization
makeData(ClusterGenerator, String[]) - Static method in class weka.datagenerators.ClusterGenerator
  Calls the data generator.
makeData(Generator, String[]) - Static method in class weka.datagenerators.Generator
  Calls the data generator.
MakeDecList - Class in weka.classifiers.rules.part
  Class for handling a decision list.
MakeDecList(ModelSelection, int) - Constructor for class weka.classifiers.rules.part.MakeDecList
  Constructor for unpruned dec list.
MakeDecList(ModelSelection, double, int) - Constructor for class weka.classifiers.rules.part.MakeDecList
  Constructor for dec list pruned using C4.5 pruning.
MakeDecList(ModelSelection, int, int, int) - Constructor for class weka.classifiers.rules.part.MakeDecList
  Constructor for dec list pruned using hold-out pruning.
MakeDensityBasedClusterer - Class in weka.clusterers
  Class for wrapping a Clusterer to make it return a distribution and density.
MakeDensityBasedClusterer() - Constructor for class weka.clusterers.MakeDensityBasedClusterer
  Default constructor.
MakeDensityBasedClusterer(Clusterer) - Constructor for class weka.clusterers.MakeDensityBasedClusterer
  Contructs a MakeDensityBasedClusterer wrapping a given Clusterer.
makeDistribution(double, int) - Static method in class weka.classifiers.evaluation.NominalPrediction
  Convert a single prediction into a probability distribution with all zero probabilities except the predicted value which has probability 1.0.
MakeIndicator - Class in weka.filters.unsupervised.attribute
  Creates a new dataset with a boolean attribute replacing a nominal attribute.
MakeIndicator() - Constructor for class weka.filters.unsupervised.attribute.MakeIndicator
makeUniformDistribution(int) - Static method in class weka.classifiers.evaluation.NominalPrediction
  Creates a uniform probability distribution -- where each of the possible classes is assigned equal probability.
makeVaryNode(int, FastVector, Instances) - Static method in class weka.classifiers.bayes.net.ADNode
  create sub tree
makeWeighted(CostMatrix) - Method in class weka.classifiers.evaluation.ConfusionMatrix
  Makes a copy of this ConfusionMatrix after applying the supplied CostMatrix to the cells.
map(String, String) - Method in class weka.classifiers.functions.pace.DoubleVector
  Applies a method to the vector
margin() - Method in class weka.classifiers.evaluation.NominalPrediction
  Calculates the prediction margin.
MarginCurve - Class in weka.classifiers.evaluation
  Generates points illustrating the prediction margin.
MarginCurve() - Constructor for class weka.classifiers.evaluation.MarginCurve
markovBlanketClassifierTipText() - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
markovBlanketClassifierTipText() - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
Matchable - Interface in weka.core
  Interface to something that can be matched with tree matching algorithms.
matchMissingValuesTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithValues
  Returns the tip text for this property
Maths - Class in weka.classifiers.functions.pace
  Class for some utility mathematical or statistical functions.
Maths() - Constructor for class weka.classifiers.functions.pace.Maths
Maths - Class in weka.core.matrix
  Utility class.
Maths() - Constructor for class weka.core.matrix.Maths
Matrix - Class in weka.classifiers.functions.pace
  Jama = Java Matrix class.
Matrix(int, int) - Constructor for class weka.classifiers.functions.pace.Matrix
  Construct an m-by-n matrix of zeros.
Matrix(int, int, double) - Constructor for class weka.classifiers.functions.pace.Matrix
  Construct an m-by-n constant matrix.
Matrix(double[][]) - Constructor for class weka.classifiers.functions.pace.Matrix
  Construct a matrix from a 2-D array.
Matrix(double[][], int, int) - Constructor for class weka.classifiers.functions.pace.Matrix
  Construct a matrix quickly without checking arguments.
Matrix(double[], int) - Constructor for class weka.classifiers.functions.pace.Matrix
  Construct a matrix from a one-dimensional packed array
matrix() - Method in class weka.classifiers.trees.j48.Distribution
  Returns matrix with distribution of class values.
Matrix - Class in weka.core
  Deprecated. Use instead `weka.core.matrix.Matrix` - only for backwards compatibility.
Matrix(int, int) - Constructor for class weka.core.Matrix
  Deprecated. Constructs a matrix and initializes it with default values.
Matrix(double[][]) - Constructor for class weka.core.Matrix
  Deprecated. Constructs a matrix using a given array.
Matrix(Reader) - Constructor for class weka.core.Matrix
  Deprecated. Reads a matrix from a reader.
Matrix - Class in weka.core.matrix
  Jama = Java Matrix class.
Matrix(int, int) - Constructor for class weka.core.matrix.Matrix
  Construct an m-by-n matrix of zeros.
Matrix(int, int, double) - Constructor for class weka.core.matrix.Matrix
  Construct an m-by-n constant matrix.
Matrix(double[][]) - Constructor for class weka.core.matrix.Matrix
  Construct a matrix from a 2-D array.
Matrix(double[][], int, int) - Constructor for class weka.core.matrix.Matrix
  Construct a matrix quickly without checking arguments.
Matrix(double[], int) - Constructor for class weka.core.matrix.Matrix
  Construct a matrix from a one-dimensional packed array
Matrix(Reader) - Constructor for class weka.core.matrix.Matrix
  Reads a matrix from a reader.
MATRIX_ON_DEMAND - Static variable in class weka.classifiers.meta.CostSensitiveClassifier
MATRIX_ON_DEMAND - Static variable in class weka.classifiers.meta.MetaCost
MATRIX_SUPPLIED - Static variable in class weka.classifiers.meta.CostSensitiveClassifier
MATRIX_SUPPLIED - Static variable in class weka.classifiers.meta.MetaCost
MatrixPanel - Class in weka.gui.visualize
  This panel displays a plot matrix of the user selected attributes of a given data set.
MatrixPanel() - Constructor for class weka.gui.visualize.MatrixPanel
  Constructor
max() - Method in class weka.classifiers.functions.pace.DoubleVector
  Returns the maximum value of all elements
max - Variable in class weka.experiment.Stats
  The maximum value seen, or Double.NaN if no values seen
MAX_SHAPES - Static variable in class weka.gui.visualize.Plot2D
maxAbs() - Method in class weka.classifiers.functions.pace.PaceMatrix
  Returns the maximum absolute value of all elements
maxAbs(int, int, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Returns the maximum absolute value of some elements of a column, that is, the elements of A[i0:i1][j].
maxBag() - Method in class weka.classifiers.trees.j48.Distribution
  Returns index of bag containing maximum number of instances.
maxBoostingIterationsTipText() - Method in class weka.classifiers.functions.SimpleLogistic
  Returns the tip text for this property
maxCardinalityTipText() - Method in class weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm
maxChunkSizeTipText() - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost
maxClass() - Method in class weka.classifiers.trees.j48.Distribution
  Returns class with highest frequency over all bags.
maxClass(int) - Method in class weka.classifiers.trees.j48.Distribution
  Returns class with highest frequency for given bag.
maxCountTipText() - Method in class weka.filters.supervised.instance.SpreadSubsample
  Returns the tip text for this property
maxDepthTipText() - Method in class weka.classifiers.trees.REPTree
  Returns the tip text for this property
maxGenerationsTipText() - Method in class weka.attributeSelection.GeneticSearch
  Returns the tip text for this property
maxImpurity() - Method in class weka.classifiers.trees.m5.CorrelationSplitInfo
  Returns the impurity of this split
maxImpurity() - Method in interface weka.classifiers.trees.m5.SplitEvaluate
  Returns the impurity of this split
maxImpurity() - Method in class weka.classifiers.trees.m5.YongSplitInfo
  Returns the impurity of this split
maximumAttributeNamesTipText() - Method in class weka.attributeSelection.PrincipalComponents
  Returns the tip text for this property
maximumVariancePercentageAllowedTipText() - Method in class weka.filters.unsupervised.attribute.RemoveUseless
  Returns the tip text for this property
maxIndex(double[]) - Static method in class weka.core.Utils
  Returns index of maximum element in a given array of doubles.
maxIndex(int[]) - Static method in class weka.core.Utils
  Returns index of maximum element in a given array of integers.
maxIterationsTipText() - Method in class weka.clusterers.EM
  Returns the tip text for this property
maxIterationsTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified
  Returns the tip text for this property
maxItsTipText() - Method in class weka.classifiers.functions.Logistic
  Returns the tip text for this property
maxItsTipText() - Method in class weka.classifiers.functions.RBFNetwork
  Returns the tip text for this property
maxKTipText() - Method in class weka.classifiers.functions.VotedPerceptron
  Returns the tip text for this property
maxNrOfParentsTipText() - Method in class weka.classifiers.bayes.net.search.SearchAlgorithm
maxParentSetSize(int) - Method in class weka.classifiers.bayes.net.ParentSet
  reserve memory for parent set
maxStaleTipText() - Method in class weka.classifiers.rules.DecisionTable
  Returns the tip text for this property
MDL - Static variable in interface weka.classifiers.bayes.net.search.local.Scoreable
mean(double[]) - Static method in class weka.core.Utils
  Computes the mean for an array of doubles.
mean - Variable in class weka.experiment.Stats
  The mean of values at the last calculateDerived() call
meanAbsoluteError() - Method in class weka.classifiers.Evaluation
  Returns the mean absolute error.
meanOrMode(int) - Method in class weka.core.Instances
  Returns the mean (mode) for a numeric (nominal) attribute as a floating-point value.
meanOrMode(Attribute) - Method in class weka.core.Instances
  Returns the mean (mode) for a numeric (nominal) attribute as a floating-point value.
meanPriorAbsoluteError() - Method in class weka.classifiers.Evaluation
  Returns the mean absolute error of the prior.
meanSquaredTipText() - Method in class weka.classifiers.lazy.IBk
  Returns the tip text for this property
measureAICScore() - Method in class weka.classifiers.bayes.BayesNet
measureAttributesUsed() - Method in class weka.classifiers.functions.SimpleLogistic
  Returns the fraction of all attributes in the data that are used in the logistic model (in percent).
measureBayesScore() - Method in class weka.classifiers.bayes.BayesNet
measureBDeuScore() - Method in class weka.classifiers.bayes.BayesNet
measureDivergence() - Method in class weka.classifiers.bayes.BayesNet
measureEntropyScore() - Method in class weka.classifiers.bayes.BayesNet
measureExamplesProcessed() - Method in class weka.classifiers.trees.ADTree
  Returns the number of examples "counted".
measureExtraArcs() - Method in class weka.classifiers.bayes.BayesNet
measureMDLScore() - Method in class weka.classifiers.bayes.BayesNet
measureMissingArcs() - Method in class weka.classifiers.bayes.BayesNet
measureNodesExpanded() - Method in class weka.classifiers.trees.ADTree
  Returns the number of nodes expanded.
measureNumAttributesSelected() - Method in class weka.classifiers.meta.AttributeSelectedClassifier
  Additional measure --- number of attributes selected
measureNumIterations() - Method in class weka.classifiers.meta.AdditiveRegression
  return the number of iterations (base classifiers) completed
measureNumLeaves() - Method in class weka.classifiers.trees.ADTree
  Calls measure function for leaf size - the number of prediction nodes.
measureNumLeaves() - Method in class weka.classifiers.trees.J48
  Returns the number of leaves
measureNumLeaves() - Method in class weka.classifiers.trees.LMT
  Returns the number of leaves in the tree
measureNumLeaves() - Method in class weka.classifiers.trees.NBTree
  Returns the number of leaves
measureNumPredictionLeaves() - Method in class weka.classifiers.trees.ADTree
  Calls measure function for prediction leaf size - the number of prediction nodes without children.
measureNumRules() - Method in class weka.classifiers.rules.DecisionTable
  Returns the number of rules
measureNumRules() - Method in class weka.classifiers.rules.PART
  Return the number of rules.
measureNumRules() - Method in class weka.classifiers.trees.J48
  Returns the number of rules (same as number of leaves)
measureNumRules() - Method in class weka.classifiers.trees.m5.M5Base
  return the number of rules
measureNumRules() - Method in class weka.classifiers.trees.NBTree
  Returns the number of rules (same as number of leaves)
measureOutOfBagError() - Method in class weka.classifiers.meta.Bagging
  Gets the out of bag error that was calculated as the classifier was built.
measureOutOfBagError() - Method in class weka.classifiers.trees.RandomForest
  Gets the out of bag error that was calculated as the classifier was built.
measureReversedArcs() - Method in class weka.classifiers.bayes.BayesNet
measureSelectionTime() - Method in class weka.classifiers.meta.AttributeSelectedClassifier
  Additional measure --- time taken (milliseconds) to select the attributes
measureTime() - Method in class weka.classifiers.meta.AttributeSelectedClassifier
  Additional measure --- time taken (milliseconds) to select attributes and build the classifier
measureTreeSize() - Method in class weka.classifiers.trees.ADTree
  Calls measure function for tree size - the total number of nodes.
measureTreeSize() - Method in class weka.classifiers.trees.J48
  Returns the size of the tree
measureTreeSize() - Method in class weka.classifiers.trees.LMT
  Returns the size of the tree
measureTreeSize() - Method in class weka.classifiers.trees.NBTree
  Returns the size of the tree
Memory - Class in weka.core
  A little helper class for Memory management.
Memory() - Constructor for class weka.core.Memory
  initializes the memory management without GUI support
Memory(boolean) - Constructor for class weka.core.Memory
  initializes the memory management
merge(SimpleLinkedList, Comparator) - Method in class weka.associations.tertius.SimpleLinkedList
merge(ADTree) - Method in class weka.classifiers.trees.ADTree
  Merges two trees together.
merge(PredictionNode, ADTree) - Method in class weka.classifiers.trees.adtree.PredictionNode
  Merges this node with another.
mergeAllItemSets(FastVector, int, int) - Static method in class weka.associations.AprioriItemSet
  Merges all item sets in the set of (k-1)-item sets to create the (k)-item sets and updates the counters.
mergeAllItemSets(FastVector, int, int) - Static method in class weka.associations.ItemSet
  Merges all item sets in the set of (k-1)-item sets to create the (k)-item sets and updates the counters.
mergeAllItemSets(FastVector, int, int) - Static method in class weka.associations.LabeledItemSet
  Merges all item sets in the set of (k-1)-item sets to create the (k)-item sets and updates the counters.
mergeInstance(Instance) - Method in class weka.core.BinarySparseInstance
  Merges this instance with the given instance and returns the result.
mergeInstance(Instance) - Method in class weka.core.Instance
  Merges this instance with the given instance and returns the result.
mergeInstance(Instance) - Method in class weka.core.SparseInstance
  Merges this instance with the given instance and returns the result.
mergeInstances(Instances, Instances) - Static method in class weka.core.Instances
  Merges two sets of Instances together.
MergeTwoValues - Class in weka.filters.unsupervised.attribute
  Merges two values of a nominal attribute.
MergeTwoValues() - Constructor for class weka.filters.unsupervised.attribute.MergeTwoValues
MetaBean - Class in weka.gui.beans
  A meta bean that encapsulates several other regular beans, useful for grouping large KnowledgeFlows.
MetaBean() - Constructor for class weka.gui.beans.MetaBean
metaClassifierTipText() - Method in class weka.classifiers.meta.Stacking
  Returns the tip text for this property
MetaCost - Class in weka.classifiers.meta
  This metaclassifier makes its base classifier cost-sensitive using the method specified in
MetaCost() - Constructor for class weka.classifiers.meta.MetaCost
METHOD_1_AGAINST_1 - Static variable in class weka.classifiers.meta.MultiClassClassifier
METHOD_1_AGAINST_ALL - Static variable in class weka.classifiers.meta.MultiClassClassifier
  The error correction modes
METHOD_ERROR_EXHAUSTIVE - Static variable in class weka.classifiers.meta.MultiClassClassifier
METHOD_ERROR_RANDOM - Static variable in class weka.classifiers.meta.MultiClassClassifier
MethodHandler - Class in weka.core.xml
  This class handles relationships between display names of properties (or classes) and Methods that are associated with them.
MethodHandler() - Constructor for class weka.core.xml.MethodHandler
  initializes the handler
methodNameTipText() - Method in class weka.filters.unsupervised.attribute.NumericTransform
  Returns the tip text for this property
methodTipText() - Method in class weka.classifiers.meta.MultiClassClassifier
metricTypeTipText() - Method in class weka.associations.Apriori
  Returns the tip text for this property
midPoint(double, int) - Method in class weka.associations.PriorEstimation
  calculates the mid point of an interval
midPoints() - Method in class weka.associations.PriorEstimation
  split the interval [0,1] into a predefined number of intervals and calculates their mid points
min - Variable in class weka.experiment.Stats
  The minimum value seen, or Double.NaN if no values seen
minAbs(int, int, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Returns the minimum absolute value of some elements of a column, that is, the elements of A[i0:i1][j].
minBucketSizeTipText() - Method in class weka.classifiers.rules.OneR
  Returns the tip text for this property
minChunkSizeTipText() - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost
minDataDLIfDeleted(int, double, boolean) - Method in class weka.classifiers.rules.RuleStats
  Compute the minimal data description length of the ruleset if the rule in the given position is deleted.
  The min_data_DL_if_deleted = data_DL_if_deleted - potential
minDataDLIfExists(int, double, boolean) - Method in class weka.classifiers.rules.RuleStats
  Compute the minimal data description length of the ruleset if the rule in the given position is NOT deleted.
  The min_data_DL_if_n_deleted = data_DL_if_n_deleted - potential
minimizeExpectedCostTipText() - Method in class weka.classifiers.meta.CostSensitiveClassifier
minimumBucketSizeTipText() - Method in class weka.attributeSelection.OneRAttributeEval
  Returns a string for this option suitable for display in the gui as a tip text
minIndex(int[]) - Static method in class weka.core.Utils
  Returns index of minimum element in a given array of integers.
minIndex(double[]) - Static method in class weka.core.Utils
  Returns index of minimum element in a given array of doubles.
minMetricTipText() - Method in class weka.associations.Apriori
  Returns the tip text for this property
minNoTipText() - Method in class weka.classifiers.rules.ConjunctiveRule
  Returns the tip text for this property
minNoTipText() - Method in class weka.classifiers.rules.JRip
  Returns the tip text for this property
minNoTipText() - Method in class weka.classifiers.rules.Ridor
  Returns the tip text for this property
minNumInstancesTipText() - Method in class weka.classifiers.trees.LMT
  Returns the tip text for this property
minNumObjTipText() - Method in class weka.classifiers.rules.PART
  Returns the tip text for this property
minNumObjTipText() - Method in class weka.classifiers.trees.J48
  Returns the tip text for this property
minNumTipText() - Method in class weka.classifiers.trees.RandomTree
  Returns the tip text for this property
minNumTipText() - Method in class weka.classifiers.trees.REPTree
  Returns the tip text for this property
MINOR - Static variable in class weka.core.Version
  the minor version
minProb - Variable in class weka.classifiers.lazy.kstar.KStarWrapper
  used/reused to hold the smallest transformation probability
minsAndMaxs(Instances, double[][], int) - Method in class weka.classifiers.trees.j48.C45Split
  Returns the minsAndMaxs of the index.th subset.
minStdDevTipText() - Method in class weka.classifiers.functions.RBFNetwork
  Returns the tip text for this property
minStdDevTipText() - Method in class weka.clusterers.EM
  Returns the tip text for this property
minStdDevTipText() - Method in class weka.clusterers.MakeDensityBasedClusterer
  Returns the tip text for this property
minus(double) - Method in class weka.classifiers.functions.pace.DoubleVector
  Subtracts a value
minus(DoubleVector) - Method in class weka.classifiers.functions.pace.DoubleVector
  Subtracts another DoubleVector element by element
minus(Matrix) - Method in class weka.classifiers.functions.pace.Matrix
  C = A - B
minus(Matrix) - Method in class weka.core.matrix.Matrix
  C = A - B
minusEquals(double) - Method in class weka.classifiers.functions.pace.DoubleVector
  Subtracts a value in place
minusEquals(DoubleVector) - Method in class weka.classifiers.functions.pace.DoubleVector
  Subtracts another DoubleVector element by element in place
minusEquals(Matrix) - Method in class weka.classifiers.functions.pace.Matrix
  A = A - B
minusEquals(Matrix) - Method in class weka.core.matrix.Matrix
  A = A - B
minVariancePropTipText() - Method in class weka.classifiers.trees.REPTree
  Returns the tip text for this property
MISSING_SHAPE - Static variable in class weka.gui.visualize.Plot2D
MISSING_VALUE - Static variable in interface weka.classifiers.evaluation.Prediction
  Constant representing a missing value.
missingArcs(BayesNet) - Method in class weka.classifiers.bayes.net.BIFReader
  Count nr of arcs missing from other network compared to current network Note that an arc is not 'missing' if it is reversed.
missingCount - Variable in class weka.core.AttributeStats
  The number of missing values
missingMergeTipText() - Method in class weka.attributeSelection.ChiSquaredAttributeEval
  Returns the tip text for this property
missingMergeTipText() - Method in class weka.attributeSelection.GainRatioAttributeEval
  Returns the tip text for this property
missingMergeTipText() - Method in class weka.attributeSelection.InfoGainAttributeEval
  Returns the tip text for this property
missingMergeTipText() - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval
  Returns the tip text for this property
missingModeTipText() - Method in class weka.classifiers.lazy.KStar
  Returns the tip text for this property
missingSeperateTipText() - Method in class weka.attributeSelection.CfsSubsetEval
  Returns the tip text for this property
missingValue() - Static method in class weka.core.Instance
  Returns the double that codes "missing".
missingValuesTipText() - Method in class weka.associations.Tertius
  Returns the tip text for this property.
MixtureDistribution - Class in weka.classifiers.functions.pace
  Abtract class for manipulating mixture distributions.
MixtureDistribution() - Constructor for class weka.classifiers.functions.pace.MixtureDistribution
MODEL_FILE_EXTENSION - Static variable in class weka.gui.explorer.ClassifierPanel
  The filename extension that should be used for model files
MODEL_FILE_EXTENSION - Static variable in class weka.gui.explorer.ClustererPanel
  The filename extension that should be used for model files
modelDistributionForInstance(Instance) - Method in class weka.classifiers.trees.lmt.LMTNode
  Returns the class probabilities for an instance according to the logistic model at the node.
modelErrors() - Method in class weka.classifiers.trees.lmt.LMTNode
  Updates the numIncorrectModel field for all nodes.
ModelPerformanceChart - Class in weka.gui.beans
  Bean that can be used for displaying threshold curves (e.g.
ModelPerformanceChart() - Constructor for class weka.gui.beans.ModelPerformanceChart
ModelPerformanceChartBeanInfo - Class in weka.gui.beans
  Bean info class for the model performance chart
ModelPerformanceChartBeanInfo() - Constructor for class weka.gui.beans.ModelPerformanceChartBeanInfo
ModelSelection - Class in weka.classifiers.trees.j48
  Abstract class for model selection criteria.
ModelSelection() - Constructor for class weka.classifiers.trees.j48.ModelSelection
modelsToString() - Method in class weka.classifiers.trees.lmt.LMTNode
  Returns a string describing the logistic regression function at the node.
modifyHeaderTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithValues
  Returns the tip text for this property
momentumTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
mostExplainingColumn(PaceMatrix, IntVector, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Returns the index of the column that has the largest (squared) response, when each of columns pvt[ks:] is moved to become the ks-th column.
mouseClicked(MouseEvent) - Method in class weka.gui.arffviewer.ArffPanel
  Invoked when a mouse button has been pressed and released on a component
mouseClicked(MouseEvent) - Method in class weka.gui.treevisualizer.TreeVisualizer
  Does nothing.
mouseDragged(MouseEvent) - Method in class weka.gui.treevisualizer.TreeVisualizer
  Performs intermediate updates to what the user wishes to do.
mouseEntered(MouseEvent) - Method in class weka.gui.arffviewer.ArffPanel
  Invoked when the mouse enters a component.
mouseEntered(MouseEvent) - Method in class weka.gui.treevisualizer.TreeVisualizer
  Does nothing.
mouseExited(MouseEvent) - Method in class weka.gui.arffviewer.ArffPanel
  Invoked when the mouse exits a component
mouseExited(MouseEvent) - Method in class weka.gui.treevisualizer.TreeVisualizer
  Does nothing.
mouseMoved(MouseEvent) - Method in class weka.gui.treevisualizer.TreeVisualizer
  Does nothing.
mousePressed(MouseEvent) - Method in class weka.gui.arffviewer.ArffPanel
  Invoked when a mouse button has been pressed on a component
mousePressed(MouseEvent) - Method in class weka.gui.treevisualizer.TreeVisualizer
  Determines what action the user wants to perform.
mouseReleased(MouseEvent) - Method in class weka.gui.arffviewer.ArffPanel
  Invoked when a mouse button has been released on a component.
mouseReleased(MouseEvent) - Method in class weka.gui.treevisualizer.TreeVisualizer
  Performs the final stages of what the user wants to perform.
MultiBoostAB - Class in weka.classifiers.meta
  Class for boosting a classifier using the MultiBoosting method.
  MultiBoosting is an extension to the highly successful AdaBoost technique for forming decision committees.
MultiBoostAB() - Constructor for class weka.classifiers.meta.MultiBoostAB
MultiClassClassifier - Class in weka.classifiers.meta
  Class for handling multi-class datasets with 2-class distribution classifiers.
MultiClassClassifier() - Constructor for class weka.classifiers.meta.MultiClassClassifier
  Constructor.
MultilayerPerceptron - Class in weka.classifiers.functions
  A Classifier that uses backpropagation to classify instances.
MultilayerPerceptron() - Constructor for class weka.classifiers.functions.MultilayerPerceptron
  The constructor.
MultiNomialBMAEstimator - Class in weka.classifiers.bayes.net.estimate
MultiNomialBMAEstimator() - Constructor for class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator
MultipleClassifiersCombiner - Class in weka.classifiers
  Abstract utility class for handling settings common to meta classifiers that build an ensemble from multiple classifiers.
MultipleClassifiersCombiner() - Constructor for class weka.classifiers.MultipleClassifiersCombiner
multiply(Matrix) - Method in class weka.core.Matrix
  Deprecated. Returns the multiplication of two matrices
multiResultsetFull(int, int) - Method in class weka.experiment.PairedTTester
  Creates a comparison table where a base resultset is compared to the other resultsets.
multiResultsetRanking(int) - Method in class weka.experiment.PairedTTester
multiResultsetSummary(int) - Method in class weka.experiment.PairedTTester
  Carries out a comparison between all resultsets, counting the number of datsets where one resultset outperforms the other.
multiResultsetWins(int, int[][]) - Method in class weka.experiment.PairedTTester
  Carries out a comparison between all resultsets, counting the number of datsets where one resultset outperforms the other.
MultiScheme - Class in weka.classifiers.meta
  Class for selecting a classifier from among several using cross validation on the training data or the performance on the training data.
MultiScheme() - Constructor for class weka.classifiers.meta.MultiScheme
mutationProbTipText() - Method in class weka.attributeSelection.GeneticSearch
  Returns the tip text for this property

## N

n2sort() - Method in class weka.gui.TableSorter
NaiveBayes - Class in weka.classifiers.bayes
  Class for a Naive Bayes classifier using estimator classes.
NaiveBayes() - Constructor for class weka.classifiers.bayes.NaiveBayes
NaiveBayes - Class in weka.classifiers.bayes.net.search.fixed
  The NaiveBayes class generates a fixed Bayes network structure with arrows from the class variable to each of the attribute variables.
NaiveBayes() - Constructor for class weka.classifiers.bayes.net.search.fixed.NaiveBayes
NaiveBayesMultinomial - Class in weka.classifiers.bayes
  The core equation for this classifier: P[Ci|D] = (P[D|Ci] x P[Ci]) / P[D] (Bayes rule) where Ci is class i and D is a document
NaiveBayesMultinomial() - Constructor for class weka.classifiers.bayes.NaiveBayesMultinomial
NaiveBayesSimple - Class in weka.classifiers.bayes
  Class for building and using a simple Naive Bayes classifier.
NaiveBayesSimple() - Constructor for class weka.classifiers.bayes.NaiveBayesSimple
NaiveBayesUpdateable - Class in weka.classifiers.bayes
  Class for a Naive Bayes classifier using estimator classes.
NaiveBayesUpdateable() - Constructor for class weka.classifiers.bayes.NaiveBayesUpdateable
name() - Method in class weka.core.Attribute
  Returns the attribute's name.
name() - Method in class weka.core.Option
  Returns the option's name.
NAME_CLASSFIRST - Static variable in class weka.experiment.xml.XMLExperiment
  the name of the classFirst property
NAME_PROPERTYNODE_PARENTCLASS - Static variable in class weka.experiment.xml.XMLExperiment
  PropertyNode member
NAME_PROPERTYNODE_PROPERTY - Static variable in class weka.experiment.xml.XMLExperiment
  PropertyNode member
NAME_PROPERTYNODE_VALUE - Static variable in class weka.experiment.xml.XMLExperiment
  PropertyNode member
NamedColor - Class in weka.gui.treevisualizer
  This class contains a color name and the rgb values of that color
NamedColor(String, int, int, int) - Constructor for class weka.gui.treevisualizer.NamedColor
nameTipText() - Method in class weka.filters.unsupervised.attribute.AddExpression
  Returns the tip text for this property
NBconditionalProb(Instance, int) - Method in class weka.classifiers.bayes.AODE
  Calculates the probability of the specified class for the given test instance, using naive Bayes.
NBTree - Class in weka.classifiers.trees
  Class for generating a Naive Bayes tree (decision tree with Naive Bayes classifiers at the leaves).
NBTree() - Constructor for class weka.classifiers.trees.NBTree
NBTreeClassifierTree - Class in weka.classifiers.trees.j48
  Class for handling a naive bayes tree structure used for classification.
NBTreeClassifierTree(ModelSelection) - Constructor for class weka.classifiers.trees.j48.NBTreeClassifierTree
NBTreeModelSelection - Class in weka.classifiers.trees.j48
  Class for selecting a NB tree split.
NBTreeModelSelection(int, Instances) - Constructor for class weka.classifiers.trees.j48.NBTreeModelSelection
  Initializes the split selection method with the given parameters.
NBTreeNoSplit - Class in weka.classifiers.trees.j48
  Class implementing a "no-split"-split (leaf node) for naive bayes trees.
NBTreeNoSplit() - Constructor for class weka.classifiers.trees.j48.NBTreeNoSplit
NBTreeSplit - Class in weka.classifiers.trees.j48
  Class implementing a NBTree split on an attribute.
NBTreeSplit(int, int, double) - Constructor for class weka.classifiers.trees.j48.NBTreeSplit
  Initializes the split model.
NDConditionalEstimator - Class in weka.estimators
  Conditional probability estimator for a numeric domain conditional upon a discrete domain (utilises separate normal estimators for each discrete conditioning value).
NDConditionalEstimator(int, double) - Constructor for class weka.estimators.NDConditionalEstimator
  Constructor
needExponentialFormat(double) - Method in class weka.classifiers.functions.pace.FlexibleDecimalFormat
NEG - Static variable in class weka.associations.tertius.Literal
negationIncludedIn(LiteralSet) - Method in class weka.associations.tertius.LiteralSet
  Test if the negation of this LiteralSet is included in another LiteralSet.
negationSatisfies(Instance) - Method in class weka.associations.tertius.AttributeValueLiteral
negationSatisfies(Instance) - Method in class weka.associations.tertius.Literal
negationTipText() - Method in class weka.associations.Tertius
  Returns the tip text for this property.
negative() - Method in class weka.associations.tertius.Literal
nestedEstimate(DoubleVector) - Method in class weka.classifiers.functions.pace.NormalMixture
  Returns the optimal nested model estimate of a vector.
NeuralConnection - Class in weka.classifiers.functions.neural
  Abstract unit in a NeuralNetwork.
NeuralConnection(String) - Constructor for class weka.classifiers.functions.neural.NeuralConnection
  Constructs The unit with the basic connection information prepared for use.
NeuralMethod - Interface in weka.classifiers.functions.neural
  This is an interface used to create classes that can be used by the neuralnode to perform all it's computations.
NeuralNode - Class in weka.classifiers.functions.neural
  This class is used to represent a node in the neuralnet.
NeuralNode(String, Random, NeuralMethod) - Constructor for class weka.classifiers.functions.neural.NeuralNode
NEW_BATCH - Static variable in class weka.gui.beans.IncrementalClassifierEvent
newDataFormat(DataSetEvent) - Method in class weka.gui.beans.ClassAssignerCustomizer
newDataFormat(DataSetEvent) - Method in class weka.gui.beans.ClassValuePickerCustomizer
newDataFormat(DataSetEvent) - Method in interface weka.gui.beans.DataFormatListener
  Recieve a DataSetEvent that encapsulates a new data format.
newDocument(String, String) - Method in class weka.core.xml.XMLDocument
  creates a new Document with the given information
newEnt(Distribution) - Method in class weka.classifiers.trees.j48.EntropyBasedSplitCrit
  Computes entropy of distribution after splitting.
newNominalRule(Attribute, Instances, int[]) - Method in class weka.classifiers.rules.OneR
  Create a rule branching on this nominal attribute.
newNumericRule(Attribute, Instances, int[]) - Method in class weka.classifiers.rules.OneR
  Create a rule branching on this numeric attribute
newRule(Attribute, Instances) - Method in class weka.classifiers.rules.OneR
  Create a rule branching on this attribute.
next() - Method in class weka.associations.tertius.SimpleLinkedList.LinkedListIterator
next(int) - Method in interface weka.classifiers.IterativeClassifier
  Performs one iteration.
next - Variable in class weka.classifiers.lazy.kstar.KStarCache.TableEntry
  next table entry (separate chaining)
next(int) - Method in class weka.classifiers.trees.ADTree
  Performs one iteration.
nextElement() - Method in class weka.core.FastVector.FastVectorEnumeration
  Returns the next element.
nextErlang(int) - Method in class weka.core.RandomVariates
  Generate a value of a variate following standard Erlang distribution.
nextExponential() - Method in class weka.core.RandomVariates
  Generate a value of a variate following standard exponential distribution using simple inverse method.
nextGamma(double) - Method in class weka.core.RandomVariates
  Generate a value of a variate following standard Gamma distribution with shape parameter a.
nextIteration() - Method in class weka.experiment.Experiment
  Carries out the next iteration of the experiment.
nextIteration() - Method in class weka.experiment.RemoteExperiment
  Overides the one in Experiment
nextSplitAddedOrder() - Method in class weka.classifiers.trees.ADTree
  Returns the next number in the order that splitter nodes have been added to the tree, and records that a new splitter has been added.
NNConditionalEstimator - Class in weka.estimators
  Conditional probability estimator for a numeric domain conditional upon a numeric domain (using Mahalanobis distance).
NNConditionalEstimator() - Constructor for class weka.estimators.NNConditionalEstimator
NNge - Class in weka.classifiers.rules
  NNge classifier.
NNge() - Constructor for class weka.classifiers.rules.NNge
nnls(PaceMatrix, IntVector) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Solves the nonnegative linear squares problem.
nnlse(PaceMatrix, PaceMatrix, PaceMatrix, IntVector) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Solves the nonnegative least squares problem with equality constraint.
nnlse1(PaceMatrix, IntVector) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Solves the nonnegative least squares problem with equality constraint.
NNMMethod - Static variable in class weka.classifiers.functions.pace.MixtureDistribution
  The nonnegative-measure-based method
NO_COMMAND - Static variable in class weka.gui.treevisualizer.TreeDisplayEvent
Node - Class in weka.gui.treevisualizer
  This class records all the data about a particular node for displaying.
Node(String, String, int, int, Color, String) - Constructor for class weka.gui.treevisualizer.Node
  This will setup all the values of the node except for its top and center.
NodePlace - Interface in weka.gui.treevisualizer
  This is an interface for classes that wish to take a node structure and arrange them
nodeToString() - Method in class weka.classifiers.trees.m5.RuleNode
  Returns a description of this node (debugging purposes)
noiseThresholdTipText() - Method in class weka.associations.Tertius
  Returns the tip text for this property.
NOMINAL - Static variable in class weka.core.Attribute
  Constant set for nominal attributes.
nominalCounts - Variable in class weka.core.AttributeStats
  Counts of each nominal value
nominalIndicesTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithValues
  Returns the tip text for this property
nominalLabelsTipText() - Method in class weka.filters.unsupervised.attribute.Add
  Returns the tip text for this property
NominalPrediction - Class in weka.classifiers.evaluation
  Encapsulates an evaluatable nominal prediction: the predicted probability distribution plus the actual class value.
NominalPrediction(double, double[]) - Constructor for class weka.classifiers.evaluation.NominalPrediction
  Creates the NominalPrediction object with a default weight of 1.0.
NominalPrediction(double, double[], double) - Constructor for class weka.classifiers.evaluation.NominalPrediction
  Creates the NominalPrediction object.
NominalToBinary - Class in weka.filters.supervised.attribute
  Converts all nominal attributes into binary numeric attributes.
NominalToBinary() - Constructor for class weka.filters.supervised.attribute.NominalToBinary
NominalToBinary - Class in weka.filters.unsupervised.attribute
  Converts all nominal attributes into binary numeric attributes.
NominalToBinary() - Constructor for class weka.filters.unsupervised.attribute.NominalToBinary
  Constructor - initialises the filter
nominalToBinaryFilterTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
NONE - Static variable in interface weka.core.converters.Saver
  The retrieval modes
NONE - Static variable in class weka.gui.visualize.VisualizePanelEvent
  No longer used
noNormalizationTipText() - Method in class weka.classifiers.lazy.IBk
  Returns the tip text for this property
NonSparseToSparse - Class in weka.filters.unsupervised.instance
  A filter that converts all incoming instances into sparse format.
NonSparseToSparse() - Constructor for class weka.filters.unsupervised.instance.NonSparseToSparse
noPruningTipText() - Method in class weka.classifiers.trees.REPTree
  Returns the tip text for this property
norm1() - Method in class weka.classifiers.functions.pace.DoubleVector
  Returns the L1-norm of the vector
norm1() - Method in class weka.classifiers.functions.pace.Matrix
  One norm
norm1() - Method in class weka.core.matrix.Matrix
  One norm
norm2() - Method in class weka.classifiers.functions.pace.DoubleVector
  Returns the L2-norm of the vector
norm2() - Method in class weka.core.matrix.Matrix
  Two norm
norm2() - Method in class weka.core.matrix.SingularValueDecomposition
  Two norm
NORM_EXPECTED_COST_NAME - Static variable in class weka.classifiers.evaluation.CostCurve
NORMAL - Static variable in interface weka.gui.graphvisualizer.GraphConstants
  NORMAL node - node actually contained in graphs description
normalDistribution - Static variable in class weka.classifiers.functions.pace.Maths
  Distribution type: noraml
NormalEstimator - Class in weka.estimators
  Simple probability estimator that places a single normal distribution over the observed values.
NormalEstimator(double) - Constructor for class weka.estimators.NormalEstimator
  Constructor that takes a precision argument.
normalInverse(double) - Static method in class weka.core.Statistics
  Returns the value, `x`, for which the area under the Normal (Gaussian) probability density function (integrated from minus infinity to `x`) is equal to the argument `y` (assumes mean is zero, variance is one).
normalize() - Method in class weka.classifiers.CostMatrix
  Normalizes the matrix so that the diagonal contains zeros.
normalize() - Method in class weka.classifiers.functions.pace.DiscreteFunction
  Normalizes the function values with L1-norm.
normalize(double[]) - Static method in class weka.core.Utils
  Normalizes the doubles in the array by their sum.
normalize(double[], double) - Static method in class weka.core.Utils
  Normalizes the doubles in the array using the given value.
Normalize - Class in weka.filters.unsupervised.attribute
  Normalizes all numeric values in the given dataset.
Normalize() - Constructor for class weka.filters.unsupervised.attribute.Normalize
Normalize - Class in weka.filters.unsupervised.instance
  This filter normalize all instances of a dataset to have a given norm.
Normalize() - Constructor for class weka.filters.unsupervised.instance.Normalize
normalizeAttributesTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
normalizeDocLengthTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Returns the tip text for this property
NormalizedPolyKernel - Class in weka.classifiers.functions.supportVector
  The normalized polynomial kernel.
NormalizedPolyKernel(Instances, int, double, boolean) - Constructor for class weka.classifiers.functions.supportVector.NormalizedPolyKernel
  Creates a new `NormalizedPolyKernel` instance.
normalizeNumericClassTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
normalizeTipText() - Method in class weka.attributeSelection.PrincipalComponents
  Returns the tip text for this property
normalizeWordWeightsTipText() - Method in class weka.classifiers.bayes.ComplementNaiveBayes
  Returns the tip text for this property
NormalMixture - Class in weka.classifiers.functions.pace
  Class for manipulating normal mixture distributions.
NormalMixture() - Constructor for class weka.classifiers.functions.pace.NormalMixture
  Contructs an empty NormalMixture
normalProbability(double) - Static method in class weka.core.Statistics
  Returns the area under the Normal (Gaussian) probability density function, integrated from minus infinity to `x` (assumes mean is zero, variance is one).
normF() - Method in class weka.classifiers.functions.pace.Matrix
  Frobenius norm
normF() - Method in class weka.core.matrix.Matrix
  Frobenius norm
normInf() - Method in class weka.classifiers.functions.pace.Matrix
  Infinity norm
normInf() - Method in class weka.core.matrix.Matrix
  Infinity norm
normTipText() - Method in class weka.filters.unsupervised.instance.Normalize
  Returns the tip text for this property
NORTH_CONNECTOR - Static variable in class weka.gui.beans.BeanVisual
NoSplit - Class in weka.classifiers.trees.j48
  Class implementing a "no-split"-split.
NoSplit(Distribution) - Constructor for class weka.classifiers.trees.j48.NoSplit
  Creates "no-split"-split for given distribution.
NoSupportForMissingValuesException - Exception in weka.core
  Exception that is raised by an object that is unable to process data with missing values.
NoSupportForMissingValuesException() - Constructor for exception weka.core.NoSupportForMissingValuesException
  Creates a new NoSupportForMissingValuesException with no message.
NoSupportForMissingValuesException(String) - Constructor for exception weka.core.NoSupportForMissingValuesException
  Creates a new NoSupportForMissingValuesException.
NOT_DRAWABLE - Static variable in interface weka.core.Drawable
notCoveredInstances() - Method in class weka.classifiers.trees.m5.Rule
  Get the instances not covered by this rule
notifyListener() - Method in class weka.gui.arffviewer.ArffPanel
  notfies all listener of the change
notifyListener(TableModelEvent) - Method in class weka.gui.arffviewer.ArffTableModel
  notfies all listener of the change of the model
notifyListener(TableModelEvent) - Method in class weka.gui.arffviewer.ArffTableSorter
  notfies all listener of the change of the model
NullFilter - Class in weka.filters
  A simple instance filter that allows no instances to pass through.
NullFilter() - Constructor for class weka.filters.NullFilter
NUM_RAND_COLS - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
numAllConditions(Instances) - Static method in class weka.classifiers.rules.RuleStats
  Compute the number of all possible conditions that could appear in a rule of a given data.
numAntdsTipText() - Method in class weka.classifiers.rules.ConjunctiveRule
  Returns the tip text for this property
numArguments() - Method in class weka.core.Option
  Returns the option's number of arguments.
numAttemptsOfGeneOptionTipText() - Method in class weka.classifiers.rules.NNge
  Returns the tip text for this property
numAttributes() - Method in class weka.core.Instance
  Returns the number of attributes.
numAttributes() - Method in class weka.core.Instances
  Returns the number of attributes.
numAttributes() - Method in class weka.core.SparseInstance
  Returns the number of attributes.
numBags() - Method in class weka.classifiers.trees.j48.Distribution
  Returns number of bags.
numberAttributesSelected() - Method in class weka.attributeSelection.AttributeSelection
  Return the number of attributes selected from the most recent run of attribute selection
numberLiteralsTipText() - Method in class weka.associations.Tertius
  Returns the tip text for this property.
numberOfAttributesTipText() - Method in class weka.filters.unsupervised.attribute.RandomProjection
  Returns the tip text for this property
numberOfClusters() - Method in class weka.clusterers.Clusterer
  Returns the number of clusters.
numberOfClusters() - Method in class weka.clusterers.Cobweb
  Returns the number of clusters.
numberOfClusters() - Method in class weka.clusterers.EM
  Returns the number of clusters.
numberOfClusters() - Method in class weka.clusterers.FarthestFirst
  Returns the number of clusters.
numberOfClusters() - Method in class weka.clusterers.MakeDensityBasedClusterer
  Returns the number of clusters.
numberOfClusters() - Method in class weka.clusterers.SimpleKMeans
  Returns the number of clusters.
NumberOfClustersRequestable - Interface in weka.clusterers
  Interface to a clusterer that can generate a requested number of clusters
numberOfLinearModels() - Method in class weka.classifiers.trees.m5.RuleNode
  Get the number of linear models in the tree
numBinsTipText() - Method in class weka.classifiers.meta.RegressionByDiscretization
  Returns the tip text for this property
numBoostingIterationsTipText() - Method in class weka.classifiers.functions.SimpleLogistic
  Returns the tip text for this property
numBoostingIterationsTipText() - Method in class weka.classifiers.trees.LMT
  Returns the tip text for this property
numCacheHits() - Method in class weka.classifiers.functions.supportVector.CachedKernel
  Returns the number of cache hits on dot products.
numCacheHits() - Method in class weka.classifiers.functions.supportVector.Kernel
  Returns the number of dot product cache hits.
numChildren() - Method in class weka.gui.HierarchyPropertyParser
  The number of the children nodes.
numClassAttributeValues() - Method in class weka.classifiers.functions.SMO
numClasses() - Method in class weka.classifiers.trees.j48.Distribution
  Returns number of classes.
numClasses() - Method in class weka.core.Instance
  Returns the number of class labels.
numClasses() - Method in class weka.core.Instances
  Returns the number of class labels.
numClustersTipText() - Method in class weka.classifiers.functions.RBFNetwork
  Returns the tip text for this property
numClustersTipText() - Method in class weka.clusterers.EM
  Returns the tip text for this property
numClustersTipText() - Method in class weka.clusterers.FarthestFirst
  Returns the tip text for this property
numClustersTipText() - Method in class weka.clusterers.SimpleKMeans
  Returns the tip text for this property
numColumns() - Method in class weka.core.Matrix
  Deprecated. Returns the number of columns in the matrix.
numCorrect() - Method in class weka.classifiers.trees.j48.Distribution
  Returns perClass(maxClass()).
numCorrect(int) - Method in class weka.classifiers.trees.j48.Distribution
  Returns perClassPerBag(index,maxClass(index)).
numDistinctValues(int) - Method in class weka.core.Instances
  Returns the number of distinct values of a given attribute.
numDistinctValues(Attribute) - Method in class weka.core.Instances
  Returns the number of distinct values of a given attribute.
numElements() - Method in class weka.classifiers.functions.supportVector.SMOset
  Returns the number of elements in the set.
NUMERIC - Static variable in class weka.core.Attribute
  Constant set for numeric attributes.
NumericPrediction - Class in weka.classifiers.evaluation
  Encapsulates an evaluatable numeric prediction: the predicted class value plus the actual class value.
NumericPrediction(double, double) - Constructor for class weka.classifiers.evaluation.NumericPrediction
  Creates the NumericPrediction object with a default weight of 1.0.
NumericPrediction(double, double, double) - Constructor for class weka.classifiers.evaluation.NumericPrediction
  Creates the NumericPrediction object.
numericStats - Variable in class weka.core.AttributeStats
  Stats on numeric value distributions
numericTipText() - Method in class weka.filters.unsupervised.attribute.MakeIndicator
NumericToBinary - Class in weka.filters.unsupervised.attribute
  Converts all numeric attributes into binary attributes (apart from the class attribute): if the value of the numeric attribute is exactly zero, the value of the new attribute will be zero.
NumericToBinary() - Constructor for class weka.filters.unsupervised.attribute.NumericToBinary
NumericTransform - Class in weka.filters.unsupervised.attribute
  Transforms numeric attributes using a given transformation method.
NumericTransform() - Constructor for class weka.filters.unsupervised.attribute.NumericTransform
  Default constructor -- sets the default transform method to java.lang.Math.abs().
numEvals() - Method in class weka.classifiers.functions.supportVector.CachedKernel
  Returns the number of time Eval has been called.
numEvals() - Method in class weka.classifiers.functions.supportVector.Kernel
  Returns the number of kernel evaluation performed.
numFalseNegatives(int) - Method in class weka.classifiers.Evaluation
  Calculate number of false negatives with respect to a particular class.
numFalsePositives(int) - Method in class weka.classifiers.Evaluation
  Calculate number of false positives with respect to a particular class.
numFeaturesTipText() - Method in class weka.classifiers.trees.RandomForest
  Returns the tip text for this property
numFoldersMIOptionTipText() - Method in class weka.classifiers.rules.NNge
  Returns the tip text for this property
numFoldsTipText() - Method in class weka.classifiers.functions.SMO
  Returns the tip text for this property
numFoldsTipText() - Method in class weka.classifiers.meta.CVParameterSelection
  Returns the tip text for this property
numFoldsTipText() - Method in class weka.classifiers.meta.LogitBoost
  Returns the tip text for this property
numFoldsTipText() - Method in class weka.classifiers.meta.MultiScheme
  Returns the tip text for this property
numFoldsTipText() - Method in class weka.classifiers.meta.Stacking
  Returns the tip text for this property
numFoldsTipText() - Method in class weka.classifiers.rules.PART
  Returns the tip text for this property
numFoldsTipText() - Method in class weka.classifiers.trees.J48
  Returns the tip text for this property
numFoldsTipText() - Method in class weka.classifiers.trees.REPTree
  Returns the tip text for this property
numFoldsTipText() - Method in class weka.experiment.CrossValidationResultProducer
  Returns the tip text for this property
numFoldsTipText() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds
  Returns the tip text for this property
numFoldsTipText() - Method in class weka.filters.unsupervised.instance.RemoveFolds
  Returns the tip text for this property
numFoldsTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified
  Returns the tip text for this property
numIncorrect() - Method in class weka.classifiers.trees.j48.Distribution
  Returns total-numCorrect().
numIncorrect(int) - Method in class weka.classifiers.trees.j48.Distribution
  Returns perBag(index)-numCorrect(index).
numInstances() - Method in class weka.classifiers.Evaluation
  Gets the number of test instances that had a known class value (actually the sum of the weights of test instances with known class value).
numInstances() - Method in class weka.core.Instances
  Returns the number of instances in the dataset.
numIterationsTipText() - Method in class weka.classifiers.functions.VotedPerceptron
  Returns the tip text for this property
numIterationsTipText() - Method in class weka.classifiers.functions.Winnow
  Returns the tip text for this property
numIterationsTipText() - Method in class weka.classifiers.IteratedSingleClassifierEnhancer
  Returns the tip text for this property
numIterationsTipText() - Method in class weka.classifiers.meta.Decorate
  Returns the tip text for this property
numIterationsTipText() - Method in class weka.classifiers.meta.MetaCost
  Returns the tip text for this property
numLeaves() - Method in class weka.classifiers.trees.j48.ClassifierTree
  Returns number of leaves in tree structure.
numLeaves() - Method in class weka.classifiers.trees.lmt.LMTNode
  Returns the number of leaves (normal count).
numLeaves(int) - Method in class weka.classifiers.trees.m5.RuleNode
  Sets the leaves' numbers
numLiterals() - Method in class weka.associations.tertius.LiteralSet
  Give the number of literals in this set.
numLiterals() - Method in class weka.associations.tertius.Predicate
numLiterals() - Method in class weka.associations.tertius.Rule
  Give the number of literals in this rule.
numNeighboursTipText() - Method in class weka.attributeSelection.ReliefFAttributeEval
  Returns the tip text for this property
numNodes() - Method in class weka.classifiers.trees.j48.ClassifierTree
  Returns number of nodes in tree structure.
numNodes() - Method in class weka.classifiers.trees.lmt.LMTNode
  Returns the number of nodes.
numNodes() - Method in class weka.classifiers.trees.RandomTree
  Computes size of the tree.
numNodes() - Method in class weka.classifiers.trees.REPTree
  Computes size of the tree.
numOfBoostingIterationsTipText() - Method in class weka.classifiers.trees.ADTree
numParameters() - Method in class weka.classifiers.functions.LinearRegression
  Get the number of coefficients used in the model
numParameters() - Method in class weka.classifiers.functions.PaceRegression
  Get the number of coefficients used in the model
numParameters() - Method in class weka.classifiers.trees.m5.PreConstructedLinearModel
  Return the number of parameters (coefficients) in the linear model
numPendingOutput() - Method in class weka.filters.Filter
  Returns the number of instances pending output
numPendingOutput() - Method in class weka.filters.unsupervised.attribute.RemoveType
  Returns the number of instances pending output
numRows() - Method in class weka.core.Matrix
  Deprecated. Returns the number of rows in the matrix.
numRules() - Method in class weka.classifiers.rules.part.MakeDecList
  Outputs the number of rules in the classifier.
numRulesTipText() - Method in class weka.associations.Apriori
  Returns the tip text for this property
numRulesTipText() - Method in class weka.associations.PredictiveApriori
  Returns the tip text for this property
numRunsTipText() - Method in class weka.classifiers.meta.LogitBoost
  Returns the tip text for this property
numSubCmtysTipText() - Method in class weka.classifiers.meta.MultiBoostAB
  Returns the tip text for this property
numSubsets() - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
  Returns the number of created subsets for the split.
numToSelectTipText() - Method in class weka.attributeSelection.GreedyStepwise
  Returns the tip text for this property
numToSelectTipText() - Method in class weka.attributeSelection.RaceSearch
  Returns the tip text for this property
numToSelectTipText() - Method in class weka.attributeSelection.Ranker
  Returns the tip text for this property
numTreesTipText() - Method in class weka.classifiers.trees.RandomForest
  Returns the tip text for this property
numTrueNegatives(int) - Method in class weka.classifiers.Evaluation
  Calculate the number of true negatives with respect to a particular class.
numTruePositives(int) - Method in class weka.classifiers.Evaluation
  Calculate the number of true positives with respect to a particular class.
numValues() - Method in class weka.core.Attribute
  Returns the number of attribute values.
numValues() - Method in class weka.core.Instance
  Returns the number of values present.
numValues() - Method in class weka.core.SparseInstance
  Returns the number of values in the sparse vector.
numXValFoldsTipText() - Method in class weka.classifiers.meta.ThresholdSelector

## O

Obfuscate - Class in weka.filters.unsupervised.attribute
  A simple instance filter that renames the relation, all attribute names and all nominal (and string) attribute values.
Obfuscate() - Constructor for class weka.filters.unsupervised.attribute.Obfuscate
observedComparator - Static variable in class weka.associations.tertius.Rule
  Comparator used to compare two rules according to their observed number of counter-instances.
obtainVotes(Instance) - Method in class weka.classifiers.functions.SMO
  Returns an array of votes for the given instance.
OFF - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
oldEnt(Distribution) - Method in class weka.classifiers.trees.j48.EntropyBasedSplitCrit
  Computes entropy of distribution before splitting.
ON - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
  Some usefull constants
onDemandDirectoryTipText() - Method in class weka.classifiers.meta.CostSensitiveClassifier
onDemandDirectoryTipText() - Method in class weka.classifiers.meta.MetaCost
  Returns the tip text for this property
onDemandDirectoryTipText() - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator
  Returns the tip text for this property
OneR - Class in weka.classifiers.rules
  Class for building and using a 1R classifier.
OneR() - Constructor for class weka.classifiers.rules.OneR
OneRAttributeEval - Class in weka.attributeSelection
  Class for Evaluating attributes individually by using the OneR classifier.
OneRAttributeEval() - Constructor for class weka.attributeSelection.OneRAttributeEval
  Constructor
onlyAlphabeticTokensTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Returns the tip text for this property.
onUnit(Graphics, int, int, int, int) - Method in class weka.classifiers.functions.neural.NeuralConnection
  Call this function to determine if the point at x,y is on the unit.
openFrame(String) - Method in class weka.gui.ResultHistoryPanel
  Opens the named result in a separate frame.
optimisticComparator - Static variable in class weka.associations.tertius.Rule
  Comparator used to compare two rules according to their optimistic estimate.
optimisticThenObservedComparator - Static variable in class weka.associations.tertius.Rule
  Comparator used to compare two rules according to their optimistic estimate and then their observed number of counter-instances.
Optimization - Class in weka.core
  Implementation of Active-sets method with BFGS update to solve optimization problem with only bounds constraints in multi-dimensions.
Optimization() - Constructor for class weka.core.Optimization
optimizationsTipText() - Method in class weka.classifiers.rules.JRip
  Returns the tip text for this property
OPTIMIZE_0 - Static variable in class weka.classifiers.meta.ThresholdSelector
OPTIMIZE_1 - Static variable in class weka.classifiers.meta.ThresholdSelector
OPTIMIZE_LFREQ - Static variable in class weka.classifiers.meta.ThresholdSelector
OPTIMIZE_MFREQ - Static variable in class weka.classifiers.meta.ThresholdSelector
OPTIMIZE_POS_NAME - Static variable in class weka.classifiers.meta.ThresholdSelector
Option - Class in weka.core
  Class to store information about an option.
Option(String, String, int, String) - Constructor for class weka.core.Option
  Creates new option with the given parameters.
OptionHandler - Interface in weka.core
  Interface to something that understands options.
orderAdded - Variable in class weka.classifiers.trees.adtree.Splitter
  The number this node was in the order of nodes added to the tree
ORDERED - Static variable in class weka.datagenerators.BIRCHCluster
ordering() - Method in class weka.core.Attribute
  Returns the ordering of the attribute.
ORDERING_MODULO - Static variable in class weka.core.Attribute
  Constant set for modulo-ordered attributes.
ORDERING_ORDERED - Static variable in class weka.core.Attribute
  Constant set for ordered attributes.
ORDERING_SYMBOLIC - Static variable in class weka.core.Attribute
  Constant set for symbolic attributes.
OrdinalClassClassifier - Class in weka.classifiers.meta
  Meta classifier for transforming an ordinal class problem to a series of binary class problems.
OrdinalClassClassifier() - Constructor for class weka.classifiers.meta.OrdinalClassClassifier
  Default constructor.
originalValue(double) - Method in class weka.filters.supervised.attribute.ClassOrder
  Return the original internal class value given the randomized class value, i.e.
OUTPUT - Static variable in class weka.classifiers.functions.neural.NeuralConnection
  This unit is an output unit.
output() - Method in class weka.filters.Filter
  Output an instance after filtering and remove from the output queue.
output() - Method in class weka.filters.unsupervised.attribute.RemoveType
  Output an instance after filtering and remove from the output queue.
outputFileName() - Method in class weka.experiment.CSVResultListener
  Get the value of OutputFileName.
outputFileTipText() - Method in class weka.experiment.CrossValidationResultProducer
  Returns the tip text for this property
outputFileTipText() - Method in class weka.experiment.CSVResultListener
  Returns the tip text for this property
outputFileTipText() - Method in class weka.experiment.RandomSplitResultProducer
  Returns the tip text for this property
outputFormat() - Method in class weka.filters.Filter
  Deprecated. use `getOutputFormat()` instead.
outputFormat() - Method in class weka.gui.streams.InstanceJoiner
  Gets the format of the output instances.
outputFormat() - Method in class weka.gui.streams.InstanceLoader
outputFormat() - Method in interface weka.gui.streams.InstanceProducer
OutputFormatDialog - Class in weka.gui.experiment
  A dialog for setting various output format parameters.
OutputFormatDialog(Frame) - Constructor for class weka.gui.experiment.OutputFormatDialog
  initializes the dialog with the given parent frame
outputItemSetsTipText() - Method in class weka.associations.Apriori
  Returns the tip text for this property
outputPeek() - Method in class weka.filters.Filter
  Output an instance after filtering but do not remove from the output queue.
outputPeek() - Method in class weka.filters.unsupervised.attribute.RemoveType
  Output an instance after filtering but do not remove from the output queue.
outputPeek() - Method in class weka.gui.streams.InstanceJoiner
  Output an instance after filtering but do not remove from the output queue.
outputPeek() - Method in class weka.gui.streams.InstanceLoader
outputPeek() - Method in interface weka.gui.streams.InstanceProducer
outputs(Vector) - Static method in class weka.gui.beans.BeanConnection
  Returns a vector of BeanInstances that can be considered as outputs (or the right-hand side of a sub-flow)
outputValue(NeuralNode) - Method in class weka.classifiers.functions.neural.LinearUnit
  This function calculates what the output value should be.
outputValue(boolean) - Method in class weka.classifiers.functions.neural.NeuralConnection
  Call this to get the output value of this unit.
outputValue(NeuralNode) - Method in interface weka.classifiers.functions.neural.NeuralMethod
  This function calculates what the output value should be.
outputValue(boolean) - Method in class weka.classifiers.functions.neural.NeuralNode
  Call this to get the output value of this unit.
outputValue(NeuralNode) - Method in class weka.classifiers.functions.neural.SigmoidUnit
  This function calculates what the output value should be.
outputWordCountsTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Returns the tip text for this property
OutputZipper - Class in weka.experiment
  OutputZipper writes output to either gzipped files or to a multi entry zip file.
OutputZipper(File) - Constructor for class weka.experiment.OutputZipper
  Constructor.
OVAL - Static variable in class weka.gui.visualize.VisualizePanelEvent
overFrequencyThreshold(double) - Method in class weka.associations.tertius.LiteralSet
  Test if this LiteralSet has more counter-instances than the threshold.
overFrequencyThreshold(double) - Method in class weka.associations.tertius.Rule
  Test if this rule is over the frequency threshold.

## P

pace2(DoubleVector) - Method in class weka.classifiers.functions.pace.ChisqMixture
  Returns the pace2 estimate of a vector.
pace4(DoubleVector) - Method in class weka.classifiers.functions.pace.ChisqMixture
  Returns the pace4 estimate of a vector.
pace6(double) - Method in class weka.classifiers.functions.pace.ChisqMixture
  Returns the pace6 estimate of a single value.
pace6(DoubleVector) - Method in class weka.classifiers.functions.pace.ChisqMixture
  Returns the pace6 estimate of a vector.
PaceMatrix - Class in weka.classifiers.functions.pace
  Class for matrix manipulation used for pace regression.
PaceMatrix(int, int) - Constructor for class weka.classifiers.functions.pace.PaceMatrix
  Construct an m-by-n PACE matrix of zeros.
PaceMatrix(int, int, double) - Constructor for class weka.classifiers.functions.pace.PaceMatrix
  Construct an m-by-n constant PACE matrix.
PaceMatrix(double[][]) - Constructor for class weka.classifiers.functions.pace.PaceMatrix
  Construct a PACE matrix from a 2-D array.
PaceMatrix(double[][], int, int) - Constructor for class weka.classifiers.functions.pace.PaceMatrix
  Construct a PACE matrix quickly without checking arguments.
PaceMatrix(double[], int) - Constructor for class weka.classifiers.functions.pace.PaceMatrix
  Construct a PaceMatrix from a one-dimensional packed array
PaceMatrix(DoubleVector) - Constructor for class weka.classifiers.functions.pace.PaceMatrix
  Construct a PaceMatrix with a single column from a DoubleVector
PaceMatrix(Matrix) - Constructor for class weka.classifiers.functions.pace.PaceMatrix
  Construct a PaceMatrix from a Matrix
PaceRegression - Class in weka.classifiers.functions
  Class for building pace regression linear models and using them for prediction.
PaceRegression() - Constructor for class weka.classifiers.functions.PaceRegression
padLeft(String, int) - Static method in class weka.core.Utils
  Pads a string to a specified length, inserting spaces on the left as required.
padRight(String, int) - Static method in class weka.core.Utils
  Pads a string to a specified length, inserting spaces on the right as required.
paint(Graphics) - Method in class weka.gui.SplashWindow
  Paints the image on the window.
paintComponent(Graphics) - Method in class weka.gui.AttributeVisualizationPanel
  Paints this component
paintComponent(Graphics) - Method in class weka.gui.beans.BeanVisual
paintComponent(Graphics) - Method in class weka.gui.PropertyPanel
  Paints the component, using the property editor's paint method.
paintComponent(Graphics) - Method in class weka.gui.treevisualizer.TreeVisualizer
  Updates the screen contents.
paintComponent(Graphics) - Method in class weka.gui.visualize.ClassPanel
  Renders this component
paintComponent(Graphics) - Method in class weka.gui.visualize.Plot2D
  Renders this component
paintConnections(Graphics) - Static method in class weka.gui.beans.BeanConnection
  Renders the connections and their names on the supplied graphics context
paintLabels(Graphics) - Static method in class weka.gui.beans.BeanInstance
  Renders the textual labels for the beans.
paintValue(Graphics, Rectangle) - Method in class weka.gui.CostMatrixEditor
  Paints a graphical representation of the object.
paintValue(Graphics, Rectangle) - Method in class weka.gui.FileEditor
  Paints a representation of the current Object.
paintValue(Graphics, Rectangle) - Method in class weka.gui.GenericArrayEditor
  Paints a representation of the current classifier.
paintValue(Graphics, Rectangle) - Method in class weka.gui.GenericObjectEditor
  Paints a representation of the current Object.
paintValue(Graphics, Rectangle) - Method in class weka.gui.SimpleDateFormatEditor
  Paints a graphical representation of the object.
PairedCorrectedTTester - Class in weka.experiment
  Behaves the same as PairedTTester, only it uses the corrected resampled t-test statistic.
PairedCorrectedTTester() - Constructor for class weka.experiment.PairedCorrectedTTester
PairedStats - Class in weka.experiment
  A class for storing stats on a paired comparison (t-test and correlation)
PairedStats(double) - Constructor for class weka.experiment.PairedStats
  Creates a new PairedStats object with the supplied significance level.
PairedStatsCorrected - Class in weka.experiment
  A class for storing stats on a paired comparison.
PairedStatsCorrected(double, double) - Constructor for class weka.experiment.PairedStatsCorrected
  Creates a new PairedStatsCorrected object with the supplied significance level and train/test ratio.
PairedTTester - Class in weka.experiment
  Calculates T-Test statistics on data stored in a set of instances.
PairedTTester() - Constructor for class weka.experiment.PairedTTester
pairwiseCoupling(double[][], double[][]) - Method in class weka.classifiers.functions.SMO
  Implements pairwise coupling.
parentClass - Variable in class weka.experiment.PropertyNode
  The class of the object with this property
parentNode() - Method in class weka.classifiers.trees.m5.RuleNode
  Get the parent of this node
ParentSet - Class in weka.classifiers.bayes.net
  Helper class for Bayes Network classifiers.
ParentSet() - Constructor for class weka.classifiers.bayes.net.ParentSet
  default constructor
ParentSet(int) - Constructor for class weka.classifiers.bayes.net.ParentSet
  constructor
ParentSet(ParentSet) - Constructor for class weka.classifiers.bayes.net.ParentSet
  copy constructor
parentValue() - Method in class weka.gui.HierarchyPropertyParser
  The value in the parent node.
parse() - Method in class weka.gui.graphvisualizer.BIFParser
  This method parses the string or the InputStream that we passed in through the constructor and builds up the m_nodes and m_edges vectors
parse() - Method in class weka.gui.graphvisualizer.DotParser
  This method parses the string or the InputStream that we passed in through the constructor and builds up the m_nodes and m_edges vectors
parseDate(String) - Method in class weka.core.Attribute
parseMatlab(String) - Static method in class weka.core.matrix.Matrix
  creates a matrix from the given Matlab string.
parseMatlab(String) - Static method in class weka.core.Matrix
  Deprecated. creates a matrix from the given Matlab string.
PART - Class in weka.classifiers.rules
  Class for generating a PART decision list.
PART() - Constructor for class weka.classifiers.rules.PART
PART_PROPERTY - Static variable in class weka.associations.tertius.IndividualLiteral
partFileTipText() - Method in class weka.associations.Tertius
  Returns the tip text for this property.
partition(Instances, int) - Static method in class weka.classifiers.rules.RuleStats
  Patition the data into 2, first of which has (numFolds-1)/numFolds of the data and the second has 1/numFolds of the data
partitionOptions(String[]) - Static method in class weka.classifiers.bayes.BayesNet
  Returns the secondary set of options (if any) contained in the supplied options array.
partitionOptions(String[]) - Static method in class weka.core.Utils
  Returns the secondary set of options (if any) contained in the supplied options array.
passesTest(Instance) - Method in class weka.datagenerators.Test
  Determines whether an instance passes the test.
passwordTipText() - Method in class weka.core.converters.DatabaseLoader
  the tip text for this property
passwordTipText() - Method in class weka.core.converters.DatabaseSaver
  Returns the tip text fo this property
passwordTipText() - Method in class weka.experiment.DatabaseUtils
  Returns the tip text for this property
pattern(int, int) - Static method in class weka.classifiers.functions.pace.FloatingPointFormat
pchisq(double) - Static method in class weka.classifiers.functions.pace.Maths
  Returns the cumulative probability of the Chi-squared distribution
pchisq(double, double) - Static method in class weka.classifiers.functions.pace.Maths
  Returns the cumulative probability of the noncentral Chi-squared distribution.
pchisq(double, DoubleVector) - Static method in class weka.classifiers.functions.pace.Maths
  Returns the cumulative probability of a set of noncentral Chi-squared distributions.
pctCorrect() - Method in class weka.classifiers.Evaluation
  Gets the percentage of instances correctly classified (that is, for which a correct prediction was made).
pctIncorrect() - Method in class weka.classifiers.Evaluation
  Gets the percentage of instances incorrectly classified (that is, for which an incorrect prediction was made).
pctUnclassified() - Method in class weka.classifiers.Evaluation
  Gets the percentage of instances not classified (that is, for which no prediction was made by the classifier).
peek() - Method in class weka.core.Queue
  Gets object from the front of the queue.
perBag(int) - Method in class weka.classifiers.trees.j48.Distribution
  Returns number of (possibly fractional) instances in given bag.
percentageTipText() - Method in class weka.filters.unsupervised.instance.RemovePercentage
  Returns the tip text for this property
percentAttributesUsed() - Method in class weka.classifiers.trees.lmt.LogisticBase
  Returns the fraction of all attributes in the data that are used in the logistic model (in percent).
percentThresholdTipText() - Method in class weka.attributeSelection.SVMAttributeEval
  Returns a tip text for this property suitable for display in the GUI
percentTipText() - Method in class weka.filters.unsupervised.attribute.AddNoise
  Returns the tip text for this property
percentTipText() - Method in class weka.filters.unsupervised.attribute.RandomProjection
  Returns the tip text for this property
percentToEliminatePerIterationTipText() - Method in class weka.attributeSelection.SVMAttributeEval
  Returns a tip text for this property suitable for display in the GUI
perClass(int) - Method in class weka.classifiers.trees.j48.Distribution
  Returns number of (possibly fractional) instances of given class.
perClassPerBag(int, int) - Method in class weka.classifiers.trees.j48.Distribution
  Returns number of (possibly fractional) instances of given class in given bag.
performRequest(String) - Method in class weka.gui.beans.AttributeSummarizer
  Perform a named user request
performRequest(String) - Method in class weka.gui.beans.Classifier
  Perform a particular request
performRequest(String) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator
  Perform the named request
performRequest(String) - Method in class weka.gui.beans.Clusterer
  Perform a particular request
performRequest(String) - Method in class weka.gui.beans.ClustererPerformanceEvaluator
  Perform the named request
performRequest(String) - Method in class weka.gui.beans.CrossValidationFoldMaker
  Perform the named request
performRequest(String) - Method in class weka.gui.beans.DataVisualizer
  Describe `performRequest` method here.
performRequest(String) - Method in class weka.gui.beans.Filter
  Perform the named request
performRequest(String) - Method in class weka.gui.beans.GraphViewer
  Perform the named request
performRequest(String) - Method in class weka.gui.beans.Loader
  Perform the named request
performRequest(String) - Method in class weka.gui.beans.MetaBean
  Perform a particular request
performRequest(String) - Method in class weka.gui.beans.ModelPerformanceChart
  Describe `performRequest` method here.
performRequest(String) - Method in class weka.gui.beans.ScatterPlotMatrix
  Perform a named user request
performRequest(String) - Method in class weka.gui.beans.StripChart
  Describe `performRequest` method here.
performRequest(String) - Method in class weka.gui.beans.TextViewer
  Perform the named request
performRequest(String) - Method in class weka.gui.beans.TrainTestSplitMaker
  Perform the named request
performRequest(String) - Method in interface weka.gui.beans.UserRequestAcceptor
  Perform the named request
phaseIID(int, int[][]) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine
  See Sugiyama et al.
phaseIIU(int, int[][]) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine
  See Sugiyama et al.
phaseIU(int, int[][]) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine
  See Sugiyama et al.
PI - Static variable in class weka.core.xml.XMLDocument
  the parsing instructions "<?xml version=\"1.0\" encoding=\"utf-8\"?>" (may not show up in Javadoc due to tags!)
PKIDiscretize - Class in weka.filters.unsupervised.attribute
  Discretizes numeric attributes using equal frequency binning where the number of bins is equal to the square root of the number of non-missing values.
PKIDiscretize() - Constructor for class weka.filters.unsupervised.attribute.PKIDiscretize
place(Node) - Method in interface weka.gui.treevisualizer.NodePlace
  The function to call to postion the tree that starts at Node r
place(Node) - Method in class weka.gui.treevisualizer.PlaceNode1
  Call this function to have each node in the tree starting at 'r' placed in a visual (not logical, they already are) tree position.
place(Node) - Method in class weka.gui.treevisualizer.PlaceNode2
  The Funtion to call to have the nodes arranged.
PlaceNode1 - Class in weka.gui.treevisualizer
  This class will place the Nodes of a tree.
PlaceNode1() - Constructor for class weka.gui.treevisualizer.PlaceNode1
PlaceNode2 - Class in weka.gui.treevisualizer
  This class will place the Nodes of a tree.
PlaceNode2() - Constructor for class weka.gui.treevisualizer.PlaceNode2
Plot2D - Class in weka.gui.visualize
  This class plots datasets in two dimensions.
Plot2D() - Constructor for class weka.gui.visualize.Plot2D
  Constructor
Plot2DCompanion - Interface in weka.gui.visualize
  Interface for classes that need to draw to the Plot2D panel *before* Plot2D renders anything (eg.
PlotData2D - Class in weka.gui.visualize
  This class is a container for plottable data.
PlotData2D(Instances) - Constructor for class weka.gui.visualize.PlotData2D
  Construct a new PlotData2D using the supplied instances
PLURAL_DUMMY - Static variable in interface weka.gui.graphvisualizer.GraphConstants
  PLURAL_DUMMY node - node with more than one outgoing edge i.e.
plus(DiscreteFunction) - Method in class weka.classifiers.functions.pace.DiscreteFunction
  Returns the combined of two discrete functions
plus(double) - Method in class weka.classifiers.functions.pace.DoubleVector
  Adds a value to all the elements
plus(DoubleVector) - Method in class weka.classifiers.functions.pace.DoubleVector
  Adds another vector element by element
plus(Matrix) - Method in class weka.classifiers.functions.pace.Matrix
  C = A + B
plus(Matrix) - Method in class weka.core.matrix.Matrix
  C = A + B
PLUS_SHAPE - Static variable in class weka.gui.visualize.Plot2D
plusEquals(DiscreteFunction) - Method in class weka.classifiers.functions.pace.DiscreteFunction
  Returns the combined of two discrete functions.
plusEquals(double) - Method in class weka.classifiers.functions.pace.DoubleVector
  Adds a value to all the elements in place
plusEquals(DoubleVector) - Method in class weka.classifiers.functions.pace.DoubleVector
  Adds another vector in place element by element
plusEquals(Matrix) - Method in class weka.classifiers.functions.pace.Matrix
  A = A + B
plusEquals(Matrix) - Method in class weka.core.matrix.Matrix
  A = A + B
pmiss - Variable in class weka.classifiers.lazy.kstar.KStarCache.TableEntry
  transformation probability to missing value
PMMethod - Static variable in class weka.classifiers.functions.pace.MixtureDistribution
  The probability-measure-based method
pnorm(double) - Static method in class weka.classifiers.functions.pace.Maths
  Returns the cumulative probability of the standard normal.
pnorm(double, double, double) - Static method in class weka.classifiers.functions.pace.Maths
  Returns the cumulative probability of a normal distribution.
pnorm(double, DoubleVector, double) - Static method in class weka.classifiers.functions.pace.Maths
  Returns the cumulative probability of a set of normal distributions with different means.
PoissonEstimator - Class in weka.estimators
  Simple probability estimator that places a single Poisson distribution over the observed values.
PoissonEstimator() - Constructor for class weka.estimators.PoissonEstimator
POLYGON - Static variable in class weka.gui.visualize.VisualizePanelEvent
PolyKernel - Class in weka.classifiers.functions.supportVector
  The polynomial kernel : K(x, y) = ^p or K(x, y) = ( +1)^p
PolyKernel(Instances, int, double, boolean) - Constructor for class weka.classifiers.functions.supportVector.PolyKernel
  Creates a new `PolyKernel` instance.
pop() - Method in class weka.core.Queue
  Pops an object from the front of the queue.
populationSizeTipText() - Method in class weka.attributeSelection.GeneticSearch
  Returns the tip text for this property
populationSizeTipText() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
populationSizeTipText() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
POS - Static variable in class weka.associations.tertius.Literal
position() - Method in class weka.classifiers.trees.m5.CorrelationSplitInfo
  Returns the position of the split in the sorted values.
position() - Method in interface weka.classifiers.trees.m5.SplitEvaluate
  Returns the position of the split in the sorted values.
position() - Method in class weka.classifiers.trees.m5.YongSplitInfo
  Returns the position of the split in the sorted values.
positive() - Method in class weka.associations.tertius.Literal
positiveDiagonal(PaceMatrix, IntVector) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Sets all diagonal elements to be positive (or nonnegative) without changing the least squares solution
postProcess(int[]) - Method in class weka.attributeSelection.ASEvaluation
  Provides a chance for a attribute evaluator to do any special post processing of the selected attribute set.
postProcess(int[]) - Method in class weka.attributeSelection.CfsSubsetEval
  Calls locallyPredictive in order to include locally predictive attributes (if requested).
postProcess(ResultProducer) - Method in class weka.experiment.AveragingResultProducer
  When this method is called, it indicates that no more results will be sent that need to be grouped together in any way.
postProcess() - Method in class weka.experiment.AveragingResultProducer
  When this method is called, it indicates that no more requests to generate results for the current experiment will be sent.
postProcess() - Method in class weka.experiment.CrossValidationResultProducer
  Perform any postprocessing.
postProcess(ResultProducer) - Method in class weka.experiment.CSVResultListener
  Perform any postprocessing.
postProcess(ResultProducer) - Method in class weka.experiment.DatabaseResultListener
  Perform any postprocessing.
postProcess(ResultProducer) - Method in class weka.experiment.DatabaseResultProducer
  When this method is called, it indicates that no more results will be sent that need to be grouped together in any way.
postProcess() - Method in class weka.experiment.DatabaseResultProducer
  When this method is called, it indicates that no more requests to generate results for the current experiment will be sent.
postProcess() - Method in class weka.experiment.Experiment
  Signals that the experiment is finished running, so that cleanup can be done.
postProcess(ResultProducer) - Method in class weka.experiment.InstancesResultListener
  Perform any postprocessing.
postProcess(ResultProducer) - Method in class weka.experiment.LearningRateResultProducer
  When this method is called, it indicates that no more results will be sent that need to be grouped together in any way.
postProcess() - Method in class weka.experiment.LearningRateResultProducer
  When this method is called, it indicates that no more requests to generate results for the current experiment will be sent.
postProcess() - Method in class weka.experiment.RandomSplitResultProducer
  Perform any postprocessing.
postProcess() - Method in class weka.experiment.RemoteExperiment
  overides the one in Experiment
postProcess(ResultProducer) - Method in interface weka.experiment.ResultListener
  Perform any postprocessing.
postProcess() - Method in interface weka.experiment.ResultProducer
  Perform any postprocessing.
PostscriptGraphics - Class in weka.gui.visualize
  The PostscriptGraphics class extends the Graphics2D class to produce an encapsulated postscript file rather than on-screen display.
PostscriptGraphics(int, int, OutputStream) - Constructor for class weka.gui.visualize.PostscriptGraphics
  Constructor Creates a new PostscriptGraphics object, given dimensions and output file.
PostscriptWriter - Class in weka.gui.visualize
  This class takes any Component and outputs it to a Postscript file.
PostscriptWriter() - Constructor for class weka.gui.visualize.PostscriptWriter
  initializes the object
PostscriptWriter(JComponent) - Constructor for class weka.gui.visualize.PostscriptWriter
  initializes the object with the given Component
PostscriptWriter(JComponent, File) - Constructor for class weka.gui.visualize.PostscriptWriter
  initializes the object with the given Component and filename
potential(int, double, double[], double[], boolean) - Method in class weka.classifiers.rules.RuleStats
  Calculate the potential to decrease DL of the ruleset, i.e.
PotentialClassIgnorer - Class in weka.filters.unsupervised.attribute
  This filter should be extended by other unsupervised attribute filters to allow processing of the class attribute if that's required.
PotentialClassIgnorer() - Constructor for class weka.filters.unsupervised.attribute.PotentialClassIgnorer
precision(int) - Method in class weka.classifiers.Evaluation
  Calculate the precision with respect to a particular class.
PRECISION_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve
PreConstructedLinearModel - Class in weka.classifiers.trees.m5
  This class encapsulates a linear regression function.
PreConstructedLinearModel(double[], double) - Constructor for class weka.classifiers.trees.m5.PreConstructedLinearModel
  Constructor
Predicate - Class in weka.associations.tertius
Predicate(String, int, boolean) - Constructor for class weka.associations.tertius.Predicate
predicted() - Method in class weka.classifiers.evaluation.NominalPrediction
  Gets the predicted class value.
predicted() - Method in class weka.classifiers.evaluation.NumericPrediction
  Gets the predicted class value.
predicted() - Method in interface weka.classifiers.evaluation.Prediction
  Gets the predicted class value.
Prediction - Interface in weka.classifiers.evaluation
  Encapsulates a single evaluatable prediction: the predicted value plus the actual class value.
PredictionAppender - Class in weka.gui.beans
  Bean that can can accept batch or incremental classifier events and produce dataset or instance events which contain instances with predictions appended.
PredictionAppender() - Constructor for class weka.gui.beans.PredictionAppender
  Creates a new `PredictionAppender` instance.
PredictionAppenderBeanInfo - Class in weka.gui.beans
  Bean info class for PredictionAppender.
PredictionAppenderBeanInfo() - Constructor for class weka.gui.beans.PredictionAppenderBeanInfo
PredictionAppenderCustomizer - Class in weka.gui.beans
  GUI Customizer for the prediction appender bean
PredictionAppenderCustomizer() - Constructor for class weka.gui.beans.PredictionAppenderCustomizer
PredictionNode - Class in weka.classifiers.trees.adtree
  Class representing a prediction node in an alternating tree.
PredictionNode(double) - Constructor for class weka.classifiers.trees.adtree.PredictionNode
  Creates a new prediction node.
PredictiveApriori - Class in weka.associations
  Class implementing the predictive apriori algorithm to mine association rules.
PredictiveApriori() - Constructor for class weka.associations.PredictiveApriori
  Constructor that allows to sets default values for the minimum confidence and the maximum number of rules the minimum confidence.
prefix() - Method in class weka.classifiers.trees.j48.ClassifierTree
  Returns tree in prefix order.
prefix() - Method in class weka.classifiers.trees.J48
  Returns tree in prefix order.
prefix() - Method in interface weka.core.Matchable
  Returns a string that describes a tree representing the object in prefix order.
premise() - Method in class weka.associations.RuleItem
  Gets the premise of a rule
prePlot(Graphics) - Method in interface weka.gui.visualize.Plot2DCompanion
  Something to be drawn before the plot itself
preProcess(ResultProducer) - Method in class weka.experiment.AveragingResultProducer
  Prepare for the results to be received.
preProcess() - Method in class weka.experiment.AveragingResultProducer
  Prepare to generate results.
preProcess() - Method in class weka.experiment.CrossValidationResultProducer
  Prepare to generate results.
preProcess(ResultProducer) - Method in class weka.experiment.CSVResultListener
  Prepare for the results to be received.
preProcess(ResultProducer) - Method in class weka.experiment.DatabaseResultListener
  Prepare for the results to be received.
preProcess(ResultProducer) - Method in class weka.experiment.DatabaseResultProducer
  Prepare for the results to be received.
preProcess() - Method in class weka.experiment.DatabaseResultProducer
  Prepare to generate results.
preProcess(ResultProducer) - Method in class weka.experiment.InstancesResultListener
  Prepare for the results to be received.
preProcess(ResultProducer) - Method in class weka.experiment.LearningRateResultProducer
  Prepare for the results to be received.
preProcess() - Method in class weka.experiment.LearningRateResultProducer
  Prepare to generate results.
preProcess() - Method in class weka.experiment.RandomSplitResultProducer
  Prepare to generate results.
preProcess(ResultProducer) - Method in interface weka.experiment.ResultListener
  Prepare for the results to be received.
preProcess() - Method in interface weka.experiment.ResultProducer
  Prepare to generate results.
PreprocessPanel - Class in weka.gui.explorer
  This panel controls simple preprocessing of instances.
PreprocessPanel() - Constructor for class weka.gui.explorer.PreprocessPanel
  Creates the instances panel with no initial instances.
previous() - Method in class weka.associations.tertius.SimpleLinkedList.LinkedListInverseIterator
PrincipalComponents - Class in weka.attributeSelection
  Class for performing principal components analysis/transformation.
PrincipalComponents() - Constructor for class weka.attributeSelection.PrincipalComponents
print() - Method in class weka.classifiers.bayes.net.ADNode
print(String) - Method in class weka.classifiers.bayes.net.VaryNode
print(int, int) - Method in class weka.classifiers.functions.pace.Matrix
  Print the matrix to stdout.
print(PrintWriter, int, int) - Method in class weka.classifiers.functions.pace.Matrix
  Print the matrix to the output stream.
print(NumberFormat, int) - Method in class weka.classifiers.functions.pace.Matrix
  Print the matrix to stdout.
print(PrintWriter, NumberFormat, int) - Method in class weka.classifiers.functions.pace.Matrix
  Print the matrix to the output stream.
print(int, int) - Method in class weka.core.matrix.Matrix
  Print the matrix to stdout.
print(PrintWriter, int, int) - Method in class weka.core.matrix.Matrix
  Print the matrix to the output stream.
print(NumberFormat, int) - Method in class weka.core.matrix.Matrix
  Print the matrix to stdout.
print(PrintWriter, NumberFormat, int) - Method in class weka.core.matrix.Matrix
  Print the matrix to the output stream.
print() - Method in class weka.core.xml.XMLDocument
  prints the current DOM document to standard out
print_hash_code() - Method in class weka.attributeSelection.ConsistencySubsetEval.hashKey
  Prints the hash code
print_hash_code() - Method in class weka.classifiers.rules.DecisionTable.hashKey
  Prints the hash code
PrintableComponent - Class in weka.gui.visualize
  This class extends the component which is handed over in the constructor by a print dialog.
PrintableComponent(JComponent) - Constructor for class weka.gui.visualize.PrintableComponent
  initializes the panel
PrintableHandler - Interface in weka.gui.visualize
  This interface is for all JComponent classes that provide the ability to print itself to a file.
PrintablePanel - Class in weka.gui.visualize
  This Panel enables the user to print the panel to various file formats.
PrintablePanel() - Constructor for class weka.gui.visualize.PrintablePanel
  initializes the panel
printAllModels() - Method in class weka.classifiers.trees.m5.RuleNode
  Print all the linear models at the learf (debugging purposes)
printElements() - Method in class weka.classifiers.functions.supportVector.SMOset
  Prints all the current elements in the set.
printFeatures() - Method in class weka.classifiers.rules.DecisionTable
  Returns a string description of the features selected
printLeafModels() - Method in class weka.classifiers.trees.j48.NBTreeClassifierTree
  Print the models at the leaves
printLeafModels() - Method in class weka.classifiers.trees.m5.RuleNode
  print all leaf models
printNodeLinearModel() - Method in class weka.classifiers.trees.m5.RuleNode
  print the linear model at this node
printOptions(String[]) - Static method in class weka.core.CheckOptionHandler
  Prints the given options to a string.
priorEntropy() - Method in class weka.classifiers.Evaluation
  Calculate the entropy of the prior distribution
PriorEstimation - Class in weka.associations
  Class implementing the prior estimattion of the predictive apriori algorithm for mining association rules.
PriorEstimation(Instances, int, int, boolean) - Constructor for class weka.associations.PriorEstimation
  Constructor
Prism - Class in weka.classifiers.rules
  Class for building and using a PRISM rule set for classifcation.
Prism() - Constructor for class weka.classifiers.rules.Prism
prob(int) - Method in class weka.classifiers.trees.j48.Distribution
  Returns relative frequency of class over all bags.
prob(int, int) - Method in class weka.classifiers.trees.j48.Distribution
  Returns relative frequency of class for given bag.
PROB_COST_FUNC_NAME - Static variable in class weka.classifiers.evaluation.CostCurve
probabilityMatrix(DoubleVector, PaceMatrix) - Method in class weka.classifiers.functions.pace.ChisqMixture
  Contructs the probability matrix for mixture estimation, given a set of support points and a set of intervals.
probabilityMatrix(DoubleVector, PaceMatrix) - Method in class weka.classifiers.functions.pace.MixtureDistribution
  Contructs the probability matrix for mixture estimation, given a set of support points and a set of intervals.
probabilityMatrix(DoubleVector, PaceMatrix) - Method in class weka.classifiers.functions.pace.NormalMixture
  Contructs the probability matrix for mixture estimation, given a set of support points and a set of intervals.
probRound(double, Random) - Static method in class weka.core.Utils
  Rounds a double to the next nearest integer value in a probabilistic fashion (e.g.
process(Instances) - Method in class weka.classifiers.CheckClassifier.PostProcessor
  Provides a hook for derived classes to further modify the data.
processClassifierPrediction(Instance, Classifier, Evaluation, FastVector, Instances, FastVector, FastVector) - Static method in class weka.gui.explorer.ClassifierPanel
  Process a classifier's prediction for an instance and update a set of plotting instances and additional plotting info.
processFile(String) - Method in class weka.classifiers.bayes.net.BIFReader
  processFile reads a BIFXML file and initializes a Bayes Net
processFilename(String) - Method in class weka.gui.Loader
  returns the processed filename, i.e.
PROCESSING - Static variable in class weka.experiment.TaskStatusInfo
processKeyString(String) - Static method in class weka.experiment.DatabaseUtils
  processes the string in such a way that it can be stored in the database, i.e., it changes backslashes into slashes and doubles single quotes.
property - Variable in class weka.experiment.PropertyNode
  Other info about the property
PROPERTY_FILE - Static variable in class weka.experiment.DatabaseUtils
  The name of the properties file
PROPERTY_FILE - Static variable in class weka.gui.experiment.ExperimenterDefaults
  The name of the properties file
PROPERTY_FILE - Static variable in class weka.gui.LookAndFeel
  The name of the properties file
propertyChange(PropertyChangeEvent) - Method in class weka.gui.beans.KnowledgeFlowApp
  Accept property change events
propertyChange(PropertyChangeEvent) - Method in class weka.gui.PropertySheetPanel
  Updates the property sheet panel with a changed property and also passed the event along.
PropertyDialog - Class in weka.gui
  Support for PropertyEditors with custom editors: puts the editor into a separate frame.
PropertyDialog(PropertyEditor, int, int) - Constructor for class weka.gui.PropertyDialog
  Creates the editor frame.
PropertyHandler - Class in weka.core.xml
  This class stores information about properties to ignore or properties that are allowed for a certain class.
PropertyHandler() - Constructor for class weka.core.xml.PropertyHandler
  initializes the handling
PropertyNode - Class in weka.experiment
  Stores information on a property of an object: the class of the object with the property; the property descriptor, and the current value.
PropertyNode(Object) - Constructor for class weka.experiment.PropertyNode
  Creates a mostly empty property.
PropertyNode(Object, PropertyDescriptor, Class) - Constructor for class weka.experiment.PropertyNode
  Creates a fully specified property node.
PropertyPanel - Class in weka.gui
  Support for drawing a property value in a component.
PropertyPanel(PropertyEditor) - Constructor for class weka.gui.PropertyPanel
  Create the panel with the supplied property editor.
PropertyPanel(PropertyEditor, boolean) - Constructor for class weka.gui.PropertyPanel
  Create the panel with the supplied property editor, optionally ignoring any custom panel the editor can provide.
PropertySelectorDialog - Class in weka.gui
  Allows the user to select any (supported) property of an object, including properties that any of it's property values may have.
PropertySelectorDialog(Frame, Object) - Constructor for class weka.gui.PropertySelectorDialog
  Create the property selection dialog.
PropertySheetPanel - Class in weka.gui
  Displays a property sheet where (supported) properties of the target object may be edited.
PropertySheetPanel() - Constructor for class weka.gui.PropertySheetPanel
  Creates the property sheet panel.
ProtectedProperties - Class in weka.core
  Simple class that extends the Properties class so that the properties are unable to be modified.
ProtectedProperties(Properties) - Constructor for class weka.core.ProtectedProperties
  Creates a set of protected properties from a set of normal ones.
prune() - Method in class weka.classifiers.trees.j48.C45PruneableClassifierTree
  Prunes a tree using C4.5's pruning procedure.
prune() - Method in class weka.classifiers.trees.j48.PruneableClassifierTree
  Prunes a tree.
prune(double) - Method in class weka.classifiers.trees.lmt.LMTNode
  Prunes a logistic model tree using the CART pruning scheme, given a cost-complexity parameter alpha.
prune(double[], double[], Instances) - Method in class weka.classifiers.trees.lmt.LMTNode
  Method for performing one fold in the cross-validation of the cost-complexity parameter.
prune() - Method in class weka.classifiers.trees.m5.RuleNode
  Recursively prune the tree
PruneableClassifierTree - Class in weka.classifiers.trees.j48
  Class for handling a tree structure that can be pruned using a pruning set.
PruneableClassifierTree(ModelSelection, boolean, int, boolean, int) - Constructor for class weka.classifiers.trees.j48.PruneableClassifierTree
  Constructor for pruneable tree structure.
PruneableDecList - Class in weka.classifiers.rules.part
  Class for handling a partial tree structure that can be pruned using a pruning set.
PruneableDecList(ModelSelection, int) - Constructor for class weka.classifiers.rules.part.PruneableDecList
  Constructor for pruneable partial tree structure.
pruneItemSets(FastVector, Hashtable) - Static method in class weka.associations.ItemSet
  Prunes a set of (k)-item sets using the given (k-1)-item sets.
pruneItemSets(FastVector, Hashtable) - Static method in class weka.associations.LabeledItemSet
  Prunes a set of (k)-item sets using the given (k-1)-item sets.
pruneRules(FastVector[], double) - Static method in class weka.associations.ItemSet
  Prunes a set of rules.
PRUNETYPE_LOGLIKELIHOOD - Static variable in class weka.classifiers.meta.RacedIncrementalLogitBoost
PRUNETYPE_NONE - Static variable in class weka.classifiers.meta.RacedIncrementalLogitBoost
  The pruning types
pruningTypeTipText() - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost
PSI - Static variable in class weka.classifiers.functions.pace.Maths
  The constant 1 / sqrt(2 pi)
PURE_INPUT - Static variable in class weka.classifiers.functions.neural.NeuralConnection
  This unit is a pure input unit.
PURE_OUTPUT - Static variable in class weka.classifiers.functions.neural.NeuralConnection
  This unit is a pure output unit.
push(Object) - Method in class weka.core.Queue
  Appends an object to the back of the queue.
put(Object, Object) - Method in class weka.core.ProtectedProperties
  Overrides a method to prevent the properties from being modified.
putAll(Map) - Method in class weka.core.ProtectedProperties
  Overrides a method to prevent the properties from being modified.
putResultInTable(String, ResultProducer, Object[], Object[]) - Method in class weka.experiment.DatabaseUtils
  Executes a database query to insert a result for the supplied key into the database.

## Q

qr() - Method in class weka.core.matrix.Matrix
  QR Decomposition
QRDecomposition - Class in weka.core.matrix
  QR Decomposition.
QRDecomposition(Matrix) - Constructor for class weka.core.matrix.QRDecomposition
  QR Decomposition, computed by Householder reflections.
queryTipText() - Method in class weka.core.converters.DatabaseLoader
  the tip text for this property
queryTipText() - Method in class weka.experiment.InstanceQuery
  Returns the tip text for this property
Queue - Class in weka.core
  Class representing a FIFO queue.
Queue() - Constructor for class weka.core.Queue
quote(String) - Static method in class weka.core.Utils
  Quotes a string if it contains special characters.

## R

RacedIncrementalLogitBoost - Class in weka.classifiers.meta
  Classifier for incremental learning of large datasets by way of racing logit-boosted committees.
RacedIncrementalLogitBoost() - Constructor for class weka.classifiers.meta.RacedIncrementalLogitBoost
  Constructor.
RaceSearch - Class in weka.attributeSelection
  Class for performing a racing search.
RaceSearch() - Constructor for class weka.attributeSelection.RaceSearch
raceTypeTipText() - Method in class weka.attributeSelection.RaceSearch
  Returns the tip text for this property
randEntropy - Variable in class weka.classifiers.lazy.kstar.KStarWrapper
  used/reused to hold the random entropy
random(int) - Static method in class weka.classifiers.functions.pace.DoubleVector
  Returns a random vector of uniform distribution
random(int, int) - Static method in class weka.classifiers.functions.pace.Matrix
  Generate matrix with random elements
random(int, int) - Static method in class weka.core.matrix.Matrix
  Generate matrix with random elements
RANDOM - Static variable in class weka.datagenerators.BIRCHCluster
RANDOM - Static variable in class weka.filters.supervised.attribute.ClassOrder
  The class values are sorted in random order
randomCARule(int, int, Random) - Method in class weka.associations.PriorEstimation
  Constructs an item set of certain length randomly.
RandomCommittee - Class in weka.classifiers.meta
  Class for creating a committee of random classifiers.
RandomCommittee() - Constructor for class weka.classifiers.meta.RandomCommittee
  Constructor.
RandomForest - Class in weka.classifiers.trees
  Class for constructing random forests.
RandomForest() - Constructor for class weka.classifiers.trees.RandomForest
Randomizable - Interface in weka.core
  Interface to something that has random behaviour that is able to be seeded with an integer.
RandomizableClassifier - Class in weka.classifiers
  Abstract utility class for handling settings common to randomizable classifiers.
RandomizableClassifier() - Constructor for class weka.classifiers.RandomizableClassifier
RandomizableIteratedSingleClassifierEnhancer - Class in weka.classifiers
  Abstract utility class for handling settings common to randomizable meta classifiers that build an ensemble from a single base learner.
RandomizableIteratedSingleClassifierEnhancer() - Constructor for class weka.classifiers.RandomizableIteratedSingleClassifierEnhancer
RandomizableMultipleClassifiersCombiner - Class in weka.classifiers
  Abstract utility class for handling settings common to randomizable meta classifiers that build an ensemble from multiple classifiers based on a given random number seed.
RandomizableMultipleClassifiersCombiner() - Constructor for class weka.classifiers.RandomizableMultipleClassifiersCombiner
RandomizableSingleClassifierEnhancer - Class in weka.classifiers
  Abstract utility class for handling settings common to randomizable meta classifiers that build an ensemble from a single base learner.
RandomizableSingleClassifierEnhancer() - Constructor for class weka.classifiers.RandomizableSingleClassifierEnhancer
randomize(int[], Random) - Method in class weka.classifiers.BVDecomposeSegCVSub
  Accepts an array of ints and randomises the values in the array, using the random seed.
randomize(Random) - Method in class weka.core.Instances
  Shuffles the instances in the set so that they are ordered randomly.
Randomize - Class in weka.filters.unsupervised.instance
  This filter randomly shuffles the order of instances passed through it.
Randomize() - Constructor for class weka.filters.unsupervised.instance.Randomize
RANDOMIZED - Static variable in class weka.datagenerators.BIRCHCluster
randomizeDataTipText() - Method in class weka.experiment.RandomSplitResultProducer
  Returns the tip text for this property
randomNormal(int, int) - Static method in class weka.classifiers.functions.pace.PaceMatrix
  Generate matrix with standard-normally distributed random elements
randomOrderTipText() - Method in class weka.classifiers.bayes.net.search.global.K2
randomOrderTipText() - Method in class weka.classifiers.bayes.net.search.local.K2
RandomProjection - Class in weka.filters.unsupervised.attribute
  Reduces the dimensionality of the data by projecting it onto a lower dimensional subspace using a random matrix with columns of unit length (It will reduce the number of attributes in the data while preserving much of its variation like PCA, but at a much less computational cost).
RandomProjection() - Constructor for class weka.filters.unsupervised.attribute.RandomProjection
randomRule(int, int, Random) - Method in class weka.associations.PriorEstimation
  Constructs an item set of certain length randomly.
RandomSearch - Class in weka.attributeSelection
  Class for performing a random search.
RandomSearch() - Constructor for class weka.attributeSelection.RandomSearch
  Constructor
randomSeedTipText() - Method in class weka.classifiers.functions.LeastMedSq
  Returns the tip text for this property
randomSeedTipText() - Method in class weka.classifiers.functions.SMO
  Returns the tip text for this property
randomSeedTipText() - Method in class weka.classifiers.trees.ADTree
randomSeedTipText() - Method in class weka.filters.supervised.instance.Resample
  Returns the tip text for this property
randomSeedTipText() - Method in class weka.filters.supervised.instance.SpreadSubsample
  Returns the tip text for this property
randomSeedTipText() - Method in class weka.filters.unsupervised.attribute.AddNoise
  Returns the tip text for this property
randomSeedTipText() - Method in class weka.filters.unsupervised.attribute.RandomProjection
  Returns the tip text for this property
randomSeedTipText() - Method in class weka.filters.unsupervised.instance.Randomize
  Returns the tip text for this property
randomSeedTipText() - Method in class weka.filters.unsupervised.instance.Resample
  Returns the tip text for this property
RandomSplitResultProducer - Class in weka.experiment
  Generates a single train/test split and calls the appropriate SplitEvaluator to generate some results.
RandomSplitResultProducer() - Constructor for class weka.experiment.RandomSplitResultProducer
RandomTree - Class in weka.classifiers.trees
  Class for constructing a tree that considers K random features at each node.
RandomTree() - Constructor for class weka.classifiers.trees.RandomTree
RandomVariates - Class in weka.core
  Class implementing some simple random variates generator.
RandomVariates() - Constructor for class weka.core.RandomVariates
  Simply the constructor of super class
RandomVariates(long) - Constructor for class weka.core.RandomVariates
  Simply the constructor of super class
randomWidthFactorTipText() - Method in class weka.classifiers.meta.MultiClassClassifier
Range - Class in weka.core
  Class representing a range of cardinal numbers.
Range() - Constructor for class weka.core.Range
  Default constructor.
Range(String) - Constructor for class weka.core.Range
  Constructor to set initial range.
RANGE_BOUNDS - Static variable in class weka.classifiers.meta.ThresholdSelector
RANGE_NONE - Static variable in class weka.classifiers.meta.ThresholdSelector
rangeCorrectionTipText() - Method in class weka.classifiers.meta.ThresholdSelector
rank() - Method in class weka.core.matrix.Matrix
  Matrix rank
rank() - Method in class weka.core.matrix.SingularValueDecomposition
  Effective numerical matrix rank
rankedAttributes() - Method in class weka.attributeSelection.AttributeSelection
  get the final ranking of the attributes.
rankedAttributes() - Method in class weka.attributeSelection.GreedyStepwise
  Produces a ranked list of attributes.
rankedAttributes() - Method in class weka.attributeSelection.RaceSearch
rankedAttributes() - Method in interface weka.attributeSelection.RankedOutputSearch
  Returns a X by 2 list of attribute indexes and corresponding evaluations from best (highest) to worst.
rankedAttributes() - Method in class weka.attributeSelection.Ranker
  Sorts the evaluated attribute list
RankedOutputSearch - Interface in weka.attributeSelection
  Interface for search methods capable of producing a ranked list of attributes.
Ranker - Class in weka.attributeSelection
  Class for ranking the attributes evaluated by a AttributeEvaluator Valid options are:
Ranker() - Constructor for class weka.attributeSelection.Ranker
  Constructor
RankSearch - Class in weka.attributeSelection
  Class for evaluating a attribute ranking (given by a specified evaluator) using a specified subset evaluator.
RankSearch() - Constructor for class weka.attributeSelection.RankSearch
rawOutputTipText() - Method in class weka.experiment.CrossValidationResultProducer
  Returns the tip text for this property
rawOutputTipText() - Method in class weka.experiment.RandomSplitResultProducer
  Returns the tip text for this property
RBFKernel - Class in weka.classifiers.functions.supportVector
  The RBF kernel.
RBFKernel(Instances, int, double) - Constructor for class weka.classifiers.functions.supportVector.RBFKernel
  Constructor.
RBFNetwork - Class in weka.classifiers.functions
  Class that implements a normalized Gaussian radial basis function network.
RBFNetwork() - Constructor for class weka.classifiers.functions.RBFNetwork
rbind(PaceMatrix) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Returns a new matrix which binds two matrices together with rows.
rchisq(int, double, Random) - Static method in class weka.classifiers.functions.pace.Maths
  Generates a sample of a Chi-square distribution.
RDG1 - Class in weka.datagenerators
  Class to generate data randomly by producing a decision list.
RDG1() - Constructor for class weka.datagenerators.RDG1
read(BufferedReader) - Static method in class weka.classifiers.functions.pace.Matrix
  Read a matrix from a stream.
read(BufferedReader) - Static method in class weka.core.matrix.Matrix
  Read a matrix from a stream.
read(String) - Static method in class weka.core.xml.KOML
  reads the XML-serialized object from the given file
read(File) - Static method in class weka.core.xml.KOML
  reads the XML-serialized object from the given file
read(InputStream) - Static method in class weka.core.xml.KOML
  reads the XML-serialized object from a stream
read(String) - Method in class weka.core.xml.XMLDocument
  parses the given XML string (can be XML or a filename) and returns a DOM Document
read(File) - Method in class weka.core.xml.XMLDocument
  parses the given file and returns a DOM document
read(InputStream) - Method in class weka.core.xml.XMLDocument
  parses the given stream and returns a DOM document
read(Reader) - Method in class weka.core.xml.XMLDocument
  parses the given reader and returns a DOM document
read(String) - Method in class weka.core.xml.XMLSerialization
  parses the given XML string (can be XML or a filename) and returns an Object generated from the representation
read(File) - Method in class weka.core.xml.XMLSerialization
  parses the given file and returns a DOM document
read(InputStream) - Method in class weka.core.xml.XMLSerialization
  parses the given stream and returns a DOM document
read(Reader) - Method in class weka.core.xml.XMLSerialization
  parses the given reader and returns a DOM document
read() - Method in class weka.core.xml.XMLSerializationMethodHandler
  returns the handler for read methods
readBeanConnection(Element) - Method in class weka.gui.beans.xml.XMLBeans
  builds the BeanConnection from the given DOM node.
readBeanInstance(Element) - Method in class weka.gui.beans.xml.XMLBeans
  builds the BeanInstance from the given DOM node.
readBeanVisual(Element) - Method in class weka.gui.beans.xml.XMLBeans
  builds the BeanVisual from the given DOM node.
readBIF(String) - Method in class weka.gui.graphvisualizer.GraphVisualizer
  BIF reader
  Reads a graph description in XMLBIF03 from a string
readBIF(InputStream) - Method in class weka.gui.graphvisualizer.GraphVisualizer
  BIF reader
  Reads a graph description in XMLBIF03 from an InputStrem
readBooleanFromXML(Element) - Method in class weka.core.xml.XMLSerialization
  builds the primitive from the given DOM node.
readByteFromXML(Element) - Method in class weka.core.xml.XMLSerialization
  builds the primitive from the given DOM node.
readCharFromXML(Element) - Method in class weka.core.xml.XMLSerialization
  builds the primitive from the given DOM node.
readCollection(Element) - Method in class weka.core.xml.XMLBasicSerialization
  builds the Collection from the given DOM node.
readColor(Element) - Method in class weka.gui.beans.xml.XMLBeans
  builds the Color from the given DOM node.
readColorUIResource(Element) - Method in class weka.gui.beans.xml.XMLBeans
  builds the ColorUIResource from the given DOM node.
readCostMatrixOld(Element) - Method in class weka.core.xml.XMLBasicSerialization
  builds the Matrix (old) from the given DOM node.
readDefaultListModel(Element) - Method in class weka.core.xml.XMLBasicSerialization
  builds the DefaultListModel from the given DOM node.
readDimension(Element) - Method in class weka.gui.beans.xml.XMLBeans
  builds the Dimension from the given DOM node.
readDOT(Reader) - Method in class weka.gui.graphvisualizer.GraphVisualizer
  Dot reader
  Reads a graph description in DOT format from a string
readDoubleFromXML(Element) - Method in class weka.core.xml.XMLSerialization
  builds the primitive from the given DOM node.
readFloatFromXML(Element) - Method in class weka.core.xml.XMLSerialization
  builds the primitive from the given DOM node.
readFont(Element) - Method in class weka.gui.beans.xml.XMLBeans
  builds the Font from the given DOM node.
readFontUIResource(Element) - Method in class weka.gui.beans.xml.XMLBeans
  builds the FontUIResource from the given DOM node.
readFromXML(Object, String, Element) - Method in class weka.core.xml.XMLSerialization
  adds the specific node to the object via a set method
readFromXML(Element) - Method in class weka.core.xml.XMLSerialization
  builds the object from the given DOM node.
readInstance(Reader) - Method in class weka.core.Instances
  Reads a single instance from the reader and appends it to the dataset.
readIntFromXML(Element) - Method in class weka.core.xml.XMLSerialization
  builds the primitive from the given DOM node.
readLoader(Element) - Method in class weka.gui.beans.xml.XMLBeans
  builds the Loader from the given DOM node.
readLongFromXML(Element) - Method in class weka.core.xml.XMLSerialization
  builds the primitive from the given DOM node.
readMap(Element) - Method in class weka.core.xml.XMLBasicSerialization
  builds the Map from the given DOM node.
readMatrix(Element) - Method in class weka.core.xml.XMLBasicSerialization
  builds the Matrix from the given DOM node.
readMatrixOld(Element) - Method in class weka.core.xml.XMLBasicSerialization
  builds the Matrix (old) from the given DOM node.
readMetaBean(Element) - Method in class weka.gui.beans.xml.XMLBeans
  builds the MetaBean from the given DOM node.
readOldFormat(Reader) - Method in class weka.classifiers.CostMatrix
  Loads a cost matrix in the old format from a reader.
readPoint(Element) - Method in class weka.gui.beans.xml.XMLBeans
  builds the Point from the given DOM node.
readProperties(String) - Static method in class weka.core.Utils
  Reads properties that inherit from three locations.
readPropertyNode(Element) - Method in class weka.experiment.xml.XMLExperiment
  builds the PropertyNode from the given DOM node.
readSaver(Element) - Method in class weka.gui.beans.xml.XMLBeans
  builds the Saver from the given DOM node.
readShortFromXML(Element) - Method in class weka.core.xml.XMLSerialization
  builds the primitive from the given DOM node.
realCount - Variable in class weka.core.AttributeStats
  The number of real-like values (i.e.
reallocateIndexes() - Method in class weka.gui.TableSorter
recall(int) - Method in class weka.classifiers.Evaluation
  Calculate the recall with respect to a particular class.
RECALL_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve
RECTANGLE - Static variable in class weka.gui.visualize.VisualizePanelEvent
reducedErrorPruningTipText() - Method in class weka.classifiers.rules.PART
  Returns the tip text for this property
reducedErrorPruningTipText() - Method in class weka.classifiers.trees.J48
  Returns the tip text for this property
reduceDimensionality(Instances) - Method in class weka.attributeSelection.AttributeSelection
  reduce the dimensionality of a set of instances to include only those attributes chosen by the last run of attribute selection.
reduceDimensionality(Instance) - Method in class weka.attributeSelection.AttributeSelection
  reduce the dimensionality of a single instance to include only those attributes chosen by the last run of attribute selection.
reduceDL(double, boolean) - Method in class weka.classifiers.rules.RuleStats
  Try to reduce the DL of the ruleset by testing removing the rules one by one in reverse order and update all the stats
reduceMatrix(double[][]) - Static method in class weka.core.ContingencyTables
  Reduces a matrix by deleting all zero rows and columns.
ReferenceInstances - Class in weka.classifiers.trees.adtree
  Simple class that extends the Instances class making it possible to create subsets of instances that reference their source set.
ReferenceInstances(Instances, int) - Constructor for class weka.classifiers.trees.adtree.ReferenceInstances
  Creates an empty set of instances.
refine(ArrayList) - Method in class weka.associations.tertius.Rule
  Refine a rule by adding literal from a set of predictes.
refresh() - Method in class weka.gui.arffviewer.ArffViewer
  validates and repaints the frame
refresh() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  validates and repaints the frame
refreshFreqTipText() - Method in class weka.gui.beans.StripChart
  GUI Tip text
register(Object, Class, String) - Method in class weka.core.xml.XMLSerializationMethodHandler
  adds read and write methods for the given class, i.e., read&;lt;name> and write<name> ("name" is prefixed by read and write)
registerEditors() - Static method in class weka.gui.GenericObjectEditor
  registers all the editors in Weka
regression(Matrix, double) - Method in class weka.core.matrix.Matrix
  Performs a (ridged) linear regression.
regression(Matrix, double[], double) - Method in class weka.core.matrix.Matrix
  Performs a weighted (ridged) linear regression.
regression(Matrix, double) - Method in class weka.core.Matrix
  Deprecated. Performs a (ridged) linear regression.
regression(Matrix, double[], double) - Method in class weka.core.Matrix
  Deprecated. Performs a weighted (ridged) linear regression.
RegressionByDiscretization - Class in weka.classifiers.meta
  Class for a regression scheme that employs any distribution classifier on a copy of the data that has the class attribute (equal-width) discretized.
RegressionByDiscretization() - Constructor for class weka.classifiers.meta.RegressionByDiscretization
  Default constructor.
RegressionSplitEvaluator - Class in weka.experiment
  A SplitEvaluator that produces results for a classification scheme on a numeric class attribute.
RegressionSplitEvaluator() - Constructor for class weka.experiment.RegressionSplitEvaluator
  No args constructor.
RELATION_NAME - Static variable in class weka.classifiers.evaluation.CostCurve
  The name of the relation used in cost curve datasets
RELATION_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve
  The name of the relation used in threshold curve datasets
relationForTableNameTipText() - Method in class weka.core.converters.DatabaseSaver
  Returns the tip text fo this property
relationName() - Method in class weka.core.Instances
  Returns the relation's name.
relativeAbsoluteError() - Method in class weka.classifiers.Evaluation
  Returns the relative absolute error.
relativeDL(int, double, boolean) - Method in class weka.classifiers.rules.RuleStats
  The description length (DL) of the ruleset relative to if the rule in the given position is deleted, which is obtained by:
  MDL if the rule exists - MDL if the rule does not exist
  Note the minimal possible DL of the ruleset is calculated(i.e.
ReliefFAttributeEval - Class in weka.attributeSelection
  Class for Evaluating attributes individually using ReliefF.
ReliefFAttributeEval() - Constructor for class weka.attributeSelection.ReliefFAttributeEval
  Constructor
RemoteBoundaryVisualizerSubTask - Class in weka.gui.boundaryvisualizer
  Class that encapsulates a sub task for distributed boundary visualization.
RemoteBoundaryVisualizerSubTask() - Constructor for class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
RemoteEngine - Class in weka.experiment
  A general purpose server for executing Task objects sent via RMI.
RemoteEngine(String) - Constructor for class weka.experiment.RemoteEngine
  Constructor
RemoteExperiment - Class in weka.experiment
  Holds all the necessary configuration information for a distributed experiment.
RemoteExperiment() - Constructor for class weka.experiment.RemoteExperiment
  Construct a new RemoteExperiment using an empty Experiment as base Experiment
RemoteExperiment(Experiment) - Constructor for class weka.experiment.RemoteExperiment
  Construct a new RemoteExperiment using a base Experiment
RemoteExperimentEvent - Class in weka.experiment
  Class encapsulating information on progress of a remote experiment
RemoteExperimentEvent(boolean, boolean, boolean, String) - Constructor for class weka.experiment.RemoteExperimentEvent
  Constructor
RemoteExperimentListener - Interface in weka.experiment
  Interface for classes that want to listen for updates on RemoteExperiment progress
remoteExperimentStatus(RemoteExperimentEvent) - Method in interface weka.experiment.RemoteExperimentListener
  Called when progress has been made in a remote experiment
RemoteExperimentSubTask - Class in weka.experiment
  Class to encapsulate an experiment as a task that can be executed on a remote host.
RemoteExperimentSubTask() - Constructor for class weka.experiment.RemoteExperimentSubTask
RemoteResult - Class in weka.gui.boundaryvisualizer
  Class that encapsulates a result (and progress info) for part of a distributed boundary visualization.
RemoteResult(int, int) - Constructor for class weka.gui.boundaryvisualizer.RemoteResult
  Creates a new `RemoteResult` instance.
remove() - Method in class weka.associations.tertius.SimpleLinkedList.LinkedListInverseIterator
remove() - Method in class weka.associations.tertius.SimpleLinkedList.LinkedListIterator
remove(Object) - Method in class weka.core.ProtectedProperties
  Overrides a method to prevent the properties from being modified.
remove(String) - Method in class weka.core.xml.MethodHandler
  removes the method for the property specified by the display name from its internal list.
remove(Class) - Method in class weka.core.xml.MethodHandler
  removes the method for the specified class from its internal list.
Remove - Class in weka.filters.unsupervised.attribute
  An instance filter that deletes a range of attributes from the dataset.
Remove() - Constructor for class weka.filters.unsupervised.attribute.Remove
  Constructor so that we can initialize the Range variable properly.
remove() - Method in class weka.gui.beans.BeanConnection
  Remove this connection
REMOVE_CHILDREN - Static variable in class weka.gui.treevisualizer.TreeDisplayEvent
removeActionListener(ActionListener) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel
  Remove a listener
removeAllBeansFromContainer(JComponent) - Static method in class weka.gui.beans.BeanInstance
  Removes all beans from containing component
removeAllElements() - Method in class weka.core.FastVector
  Removes all components from this vector and sets its size to zero.
removeAllElements() - Method in class weka.core.Queue
  Removes all objects from the queue m_Tail.m_Next.
removeAllInputs() - Method in class weka.classifiers.functions.neural.NeuralConnection
  This function will remove all the inputs to this unit.
removeAllInputs() - Method in class weka.classifiers.functions.neural.NeuralNode
  This function will remove all the inputs to this unit.
removeAllMissingColsTipText() - Method in class weka.associations.Apriori
  Returns the tip text for this property
removeAllOutputs() - Method in class weka.classifiers.functions.neural.NeuralConnection
  This function will remove all outputs to this unit.
removeAllowed(Class, String) - Method in class weka.core.xml.PropertyHandler
  removes the given property (display name) for the specified class from the list of allowed properties.
removeAllPlots() - Method in class weka.gui.visualize.Plot2D
  Clears all plots
removeBatchClassifierListener(BatchClassifierListener) - Method in class weka.gui.beans.Classifier
  Remove a batch classifier listener
removeBatchClustererListener(BatchClustererListener) - Method in class weka.gui.beans.Clusterer
  Remove a batch clusterer listener
removeBean(JComponent) - Method in class weka.gui.beans.BeanInstance
  Remove this bean from the list of beans and from the containing component
removeCancelListener(ActionListener) - Method in class weka.gui.GenericObjectEditor.GOEPanel
  This is used to remove an action listener from the cancel button
removeChangeListener(ChangeListener) - Method in class weka.gui.arffviewer.ArffPanel
  Removes a ChangeListener from the panel
removeChangeListener(ChangeListener) - Method in class weka.gui.arffviewer.ArffTable
  Removes a ChangeListener from the panel
removeChartListener(ChartListener) - Method in class weka.gui.beans.IncrementalClassifierEvaluator
  Remove a chart listener
removeConnections(BeanInstance) - Static method in class weka.gui.beans.BeanConnection
  Remove all connections for a bean.
removeDataFormatListener(DataFormatListener) - Method in class weka.gui.beans.ClassAssigner
removeDataFormatListener(DataFormatListener) - Method in class weka.gui.beans.ClassValuePicker
removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.AbstractDataSource
  Remove a listener
removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.ClassAssigner
removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.ClassValuePicker
removeDataSourceListener(DataSourceListener) - Method in interface weka.gui.beans.DataSource
  Remove a data source listener
removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Filter
  Remove a data source listener
removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Loader
  Remove a listener
removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.PredictionAppender
  Remove a datasource listener
removeElementAt(int) - Method in class weka.core.FastVector
  Deletes an element from this vector.
removeFirst() - Method in class weka.associations.tertius.SimpleLinkedList
RemoveFolds - Class in weka.filters.unsupervised.instance
  This filter takes a dataset and outputs a specified fold for cross validation.
RemoveFolds() - Constructor for class weka.filters.unsupervised.instance.RemoveFolds
removeGraphListener(GraphListener) - Method in class weka.gui.beans.Classifier
  Remove a graph listener
removeGraphListener(GraphListener) - Method in class weka.gui.beans.Clusterer
  Remove a graph listener
removeIgnored(String) - Method in class weka.core.xml.PropertyHandler
  removes the given display name from the ignore list.
removeIgnored(Class, String) - Method in class weka.core.xml.PropertyHandler
  removes the given display name from the ignore list of the class.
removeIncrementalClassifierListener(IncrementalClassifierListener) - Method in class weka.gui.beans.Classifier
  Remove an incremental classifier listener
removeInstanceListener(InstanceListener) - Method in class weka.gui.beans.AbstractDataSource
  Remove an instance listener
removeInstanceListener(InstanceListener) - Method in class weka.gui.beans.ClassAssigner
removeInstanceListener(InstanceListener) - Method in interface weka.gui.beans.DataSource
  Remove an instance listener
removeInstanceListener(InstanceListener) - Method in class weka.gui.beans.Filter
  Remove an instance listener
removeInstanceListener(InstanceListener) - Method in class weka.gui.beans.Loader
  Remove an instance listener
removeInstanceListener(InstanceListener) - Method in class weka.gui.beans.PredictionAppender
  Remove an instance listener
removeInstanceListener(InstanceListener) - Method in class weka.gui.streams.InstanceJoiner
removeInstanceListener(InstanceListener) - Method in class weka.gui.streams.InstanceLoader
removeInstanceListener(InstanceListener) - Method in interface weka.gui.streams.InstanceProducer
removeLast() - Method in class weka.classifiers.rules.RuleStats
  Remove the last rule in the ruleset as well as it's stats.
removeLayoutCompleteEventListener(LayoutCompleteEventListener) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine
  Method to remove a LayoutCompleteEventListener.
removeLayoutCompleteEventListener(LayoutCompleteEventListener) - Method in interface weka.gui.graphvisualizer.LayoutEngine
  This method removes a LayoutCompleteEventListener from the LayoutEngine.
removeLinkAt(int) - Method in class weka.attributeSelection.BestFirst.LinkedList2
  removes an element (Link) at a specific index from the list.
removeLinkAt(int) - Method in class weka.classifiers.rules.DecisionTable.LinkedList
  Removes an element (Link) at a specific index from the list.
RemoveMisclassified - Class in weka.filters.unsupervised.instance
  A filter that removes instances which are incorrectly classified.
RemoveMisclassified() - Constructor for class weka.filters.unsupervised.instance.RemoveMisclassified
removeNotify() - Method in class weka.gui.PropertyPanel
  Cleans up when the panel is destroyed.
removeOkListener(ActionListener) - Method in class weka.gui.GenericObjectEditor.GOEPanel
  This is used to remove an action listener from the ok button
RemovePercentage - Class in weka.filters.unsupervised.instance
  This filter removes a given percentage of a dataset.
RemovePercentage() - Constructor for class weka.filters.unsupervised.instance.RemovePercentage
removePropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.AbstractDataSource
  Remove a property change listener from this bean
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.BeanVisual
  Remove a property change listener
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClassAssignerCustomizer
  Remove a property change listener
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClassifierCustomizer
  Remove a property change listener
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClassValuePickerCustomizer
  Remove a property change listener
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClustererCustomizer
  Remove a property change listener
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.CrossValidationFoldMakerCustomizer
  Remove a property change listener
removePropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.DataVisualizer
  Remove a property change listener from this bean
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.FilterCustomizer
  Remove a property change listener
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.LoaderCustomizer
  Remove a property change listener
removePropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.ModelPerformanceChart
  Remove a property change listener from this bean
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.PredictionAppenderCustomizer
  Remove a property change listener
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.SaverCustomizer
  Remove a property change listener
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.StripChartCustomizer
  Remove a property change listener
removePropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.TextViewer
  Remove a property change listener from this bean
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.TrainTestSplitMakerCustomizer
  Remove a property change listener
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.CostMatrixEditor
  Removes an object from the list of those that wish to be informed when the cost matrix changes.
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.experiment.SetupPanel
  Removes a PropertyChangeListener.
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.experiment.SimpleSetupPanel
  Removes a PropertyChangeListener.
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.explorer.PreprocessPanel
  Removes a PropertyChangeListener.
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.GenericArrayEditor
  Removes a PropertyChangeListener.
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.GenericObjectEditor
  Removes a PropertyChangeListener.
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.PropertySheetPanel
  Removes a PropertyChangeListener.
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.SetInstancesPanel
  Removes a PropertyChangeListener.
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.SimpleDateFormatEditor
  Removes an object from the list of those that wish to be informed when the date format changes.
removePropertyChangeListenersSubFlow(PropertyChangeListener) - Method in class weka.gui.beans.MetaBean
RemoveRange - Class in weka.filters.unsupervised.instance
  This filter takes a dataset and removes a subset of it.
RemoveRange() - Constructor for class weka.filters.unsupervised.instance.RemoveRange
removeRedundant(RuleItem) - Method in class weka.associations.RuleGeneration
  Method that removes redundant rules out of the list of the best rules.
removeResult(String) - Method in class weka.gui.ResultHistoryPanel
  Removes one of the result buffers from the history.
removeSubstring(String, String) - Static method in class weka.core.Utils
  Removes all occurrences of a string from another string.
removeTableModelListener(TableModelListener) - Method in class weka.gui.arffviewer.ArffTableModel
  removes a listener from the list that is notified each time a change to the data model occurs
removeTableModelListener(TableModelListener) - Method in class weka.gui.arffviewer.ArffTableSorter
  removes a listener from the list that is notified each time a change to the data model occurs
removeTestSetListener(TestSetListener) - Method in class weka.gui.beans.AbstractTestSetProducer
  Remove a listener for test sets
removeTestSetListener(TestSetListener) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer
  Remove a test set listener
removeTestSetListener(TestSetListener) - Method in class weka.gui.beans.ClassAssigner
removeTestSetListener(TestSetListener) - Method in class weka.gui.beans.Filter
  Remove a test set listener
removeTestSetListener(TestSetListener) - Method in class weka.gui.beans.PredictionAppender
  Remove a test set listener
removeTestSetListener(TestSetListener) - Method in interface weka.gui.beans.TestSetProducer
  Remove a listener for test set events
removeTextListener(TextListener) - Method in class weka.gui.beans.Classifier
  Remove a text listener
removeTextListener(TextListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator
  Remove a text listener
removeTextListener(TextListener) - Method in class weka.gui.beans.Clusterer
  Remove a text listener
removeTextListener(TextListener) - Method in class weka.gui.beans.ClustererPerformanceEvaluator
  Remove a text listener
removeTextListener(TextListener) - Method in class weka.gui.beans.IncrementalClassifierEvaluator
  Remove a text listener
removeThresholdDataListener(ThresholdDataListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator
  Remove a Threshold data listener
removeTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer
  Remove a training set listener
removeTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.AbstractTrainingSetProducer
  Remove a training set listener
removeTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.ClassAssigner
removeTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.Filter
  Remove a training set listener
removeTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.PredictionAppender
  Remove a training set listener
removeTrainingSetListener(TrainingSetListener) - Method in interface weka.gui.beans.TrainingSetProducer
  Remove a training set listener
RemoveType - Class in weka.filters.unsupervised.attribute
  A filter that removes attributes of a given type.
RemoveType() - Constructor for class weka.filters.unsupervised.attribute.RemoveType
RemoveUseless - Class in weka.filters.unsupervised.attribute
  This filter removes attributes that do not vary at all or that vary too much.
RemoveUseless() - Constructor for class weka.filters.unsupervised.attribute.RemoveUseless
removeVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.AbstractDataSource
  Remove a vetoable change listener from this bean
removeVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.DataVisualizer
  Remove a vetoable change listener from this bean
removeVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.ModelPerformanceChart
  Remove a vetoable change listener from this bean
removeVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.TextViewer
  Remove a vetoable change listener from this bean
removeVisualizableErrorListener(VisualizableErrorListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator
  Remove a visualizable error listener
RemoveWithValues - Class in weka.filters.unsupervised.instance
  Filters instances according to the value of an attribute.
RemoveWithValues() - Constructor for class weka.filters.unsupervised.instance.RemoveWithValues
  Default constructor
renameAttribute(int, String) - Method in class weka.core.Instances
  Renames an attribute.
renameAttribute(Attribute, String) - Method in class weka.core.Instances
  Renames an attribute.
renameAttribute() - Method in class weka.gui.arffviewer.ArffPanel
  renames the current attribute
renameAttribute() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  renames the current selected Attribute
renameAttributeAt(int, String) - Method in class weka.gui.arffviewer.ArffTableModel
  renames the attribute at the given col index
renameAttributeAt(int, String) - Method in class weka.gui.arffviewer.ArffTableSorter
  renames the attribute at the given col index
renameAttributeValue(int, int, String) - Method in class weka.core.Instances
  Renames the value of a nominal (or string) attribute value.
renameAttributeValue(Attribute, String, String) - Method in class weka.core.Instances
  Renames the value of a nominal (or string) attribute value.
RepeatedHillClimber - Class in weka.classifiers.bayes.net.search.global
  RepeatedHillClimber searches for Bayesian network structures by repeatedly generating a random network and apply hillclimber on it.
RepeatedHillClimber() - Constructor for class weka.classifiers.bayes.net.search.global.RepeatedHillClimber
RepeatedHillClimber - Class in weka.classifiers.bayes.net.search.local
  RepeatedHillClimber searches for Bayesian network structures by repeatedly generating a random network and apply hillclimber on it.
RepeatedHillClimber() - Constructor for class weka.classifiers.bayes.net.search.local.RepeatedHillClimber
repeatLiteralsTipText() - Method in class weka.associations.Tertius
  Returns the tip text for this property.
replaceMissingValues(double[]) - Method in class weka.core.BinarySparseInstance
  Does nothing, since we don't support missing values.
replaceMissingValues(double[]) - Method in class weka.core.Instance
  Replaces all missing values in the instance with the values contained in the given array.
replaceMissingValues(double[]) - Method in class weka.core.SparseInstance
  Replaces all missing values in the instance with the values contained in the given array.
ReplaceMissingValues - Class in weka.filters.unsupervised.attribute
  Replaces all missing values for nominal and numeric attributes in a dataset with the modes and means from the training data.
ReplaceMissingValues() - Constructor for class weka.filters.unsupervised.attribute.ReplaceMissingValues
replaceMissingValuesTipText() - Method in class weka.filters.unsupervised.attribute.RandomProjection
  Returns the tip text for this property
replaceSubstring(String, String, String) - Static method in class weka.core.Utils
  Replaces with a new string, all occurrences of a string from another string.
replot() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel
  Quickly replot the display using cached probability estimates
reportFrequencyTipText() - Method in class weka.attributeSelection.GeneticSearch
  Returns the tip text for this property
REPTree - Class in weka.classifiers.trees
  Fast decision tree learner.
REPTree() - Constructor for class weka.classifiers.trees.REPTree
resample(Random) - Method in class weka.core.Instances
  Creates a new dataset of the same size using random sampling with replacement.
Resample - Class in weka.filters.supervised.instance
  Produces a random subsample of a dataset using sampling with replacement.
Resample() - Constructor for class weka.filters.supervised.instance.Resample
Resample - Class in weka.filters.unsupervised.instance
  Produces a random subsample of a dataset using sampling with replacement.
Resample() - Constructor for class weka.filters.unsupervised.instance.Resample
resampleWithWeights(Instances, Random, boolean[]) - Method in class weka.classifiers.meta.Bagging
  Creates a new dataset of the same size using random sampling with replacement according to the given weight vector.
resampleWithWeights(Random) - Method in class weka.core.Instances
  Creates a new dataset of the same size using random sampling with replacement according to the current instance weights.
resampleWithWeights(Random, double[]) - Method in class weka.core.Instances
  Creates a new dataset of the same size using random sampling with replacement according to the given weight vector.
reset() - Method in class weka.classifiers.functions.neural.NeuralConnection
  Call this to reset the unit for another run.
reset() - Method in class weka.classifiers.functions.neural.NeuralNode
  Call this to reset the value and error for this unit, ready for the next run.
reset() - Method in class weka.core.converters.AbstractLoader
  Default implementation sets retrieval mode to NONE
reset() - Method in class weka.core.converters.ArffLoader
  Resets the Loader ready to read a new data set
reset() - Method in class weka.core.converters.C45Loader
  Resets the Loader ready to read a new data set
reset() - Method in class weka.core.converters.CSVLoader
  Resets the loader ready to read a new data set
reset() - Method in class weka.core.converters.DatabaseLoader
  Resets the Loader ready to read a new data set
reset() - Method in interface weka.core.converters.Loader
  Resets the Loader object ready to begin loading.
reset() - Method in class weka.core.converters.SerializedInstancesLoader
  Resets the Loader ready to read a new data set
reset() - Static method in class weka.gui.beans.BeanConnection
  Reset the list of connections
reset(JComponent) - Static method in class weka.gui.beans.BeanInstance
  Reset the list of beans
resetAttIndex(boolean) - Method in class weka.classifiers.lazy.LBR.Indexes
  Resets the boolean value in AttIndexes array
resetAttIndexTo(LBR.Indexes) - Method in class weka.classifiers.lazy.LBR.Indexes
  Resets the boolean value in AttIndexes array based on another set of Indexes
resetDatasetBasedOn(LBR.Indexes) - Method in class weka.classifiers.lazy.LBR.Indexes
  Resets the boolean values in Attribute and Instance array to reflect an empty dataset withthe same attributes set as in the incoming Indexes Object
resetDistribution(Instances) - Method in class weka.classifiers.trees.j48.BinC45Split
  Sets distribution associated with model.
resetDistribution(Instances) - Method in class weka.classifiers.trees.j48.C45Split
  Sets distribution associated with model.
resetDistribution(Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
  Sets distribution associated with model.
resetInstanceIndex(boolean) - Method in class weka.classifiers.lazy.LBR.Indexes
  Resets the boolean value in the Instance Indexes array to a specified value
resetOptions() - Method in class weka.associations.Apriori
  Resets the options to the default values.
resetOptions() - Method in class weka.associations.PredictiveApriori
  Resets the options to the default values.
resetOptions() - Method in class weka.associations.Tertius
  Resets the options to the default values.
resetOptions() - Method in class weka.core.converters.AbstractFileSaver
  resets the options
resetOptions() - Method in class weka.core.converters.AbstractSaver
  resets the options
resetOptions() - Method in class weka.core.converters.ArffSaver
  Resets the Saver
resetOptions() - Method in class weka.core.converters.C45Saver
  Resets the Saver
resetOptions() - Method in class weka.core.converters.CSVSaver
  Resets the Saver
resetOptions() - Method in class weka.core.converters.DatabaseSaver
  Resets the Saver ready to save a new data set
resetOptions() - Method in class weka.core.converters.SerializedInstancesSaver
  Resets the Saver
resetStructure() - Method in class weka.core.converters.AbstractSaver
  Resets the structure (header information of the instances)
resetStructure() - Method in class weka.core.converters.DatabaseLoader
  Resets the structure of instances
resetTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
resetWriter() - Method in class weka.core.converters.AbstractFileSaver
  Sets the writer to null.
ResidualModelSelection - Class in weka.classifiers.trees.lmt
  Helper class for logistic model trees (weka.classifiers.trees.lmt.LMT) to implement the splitting criterion based on residuals.
ResidualModelSelection(int) - Constructor for class weka.classifiers.trees.lmt.ResidualModelSelection
  Constructor to create ResidualModelSelection object.
ResidualSplit - Class in weka.classifiers.trees.lmt
  Helper class for logistic model trees (weka.classifiers.trees.lmt.LMT) to implement the splitting criterion based on residuals of the LogitBoost algorithm.
ResidualSplit(int) - Constructor for class weka.classifiers.trees.lmt.ResidualSplit
  Creates a split object
restoreBeans() - Method in class weka.gui.beans.MetaBean
restoreWeights() - Method in class weka.classifiers.functions.neural.NeuralConnection
  Call this to have the connection restore from the saved weights.
restoreWeights() - Method in class weka.classifiers.functions.neural.NeuralNode
  Call this to have the connection restore from the saved weights.
ResultHistoryPanel - Class in weka.gui
  A component that accepts named stringbuffers and displays the name in a list box.
ResultHistoryPanel(JTextComponent) - Constructor for class weka.gui.ResultHistoryPanel
  Create the result history object
ResultHistoryPanel.RKeyAdapter - Class in weka.gui
  Extension of KeyAdapter that implements Serializable.
ResultHistoryPanel.RKeyAdapter() - Constructor for class weka.gui.ResultHistoryPanel.RKeyAdapter
ResultHistoryPanel.RMouseAdapter - Class in weka.gui
  Extension of MouseAdapter that implements Serializable.
ResultHistoryPanel.RMouseAdapter() - Constructor for class weka.gui.ResultHistoryPanel.RMouseAdapter
ResultListener - Interface in weka.experiment
  Interface for objects able to listen for results obtained by a ResultProducer
ResultProducer - Interface in weka.experiment
  This interface defines the methods required for an object that produces results for different randomizations of a dataset.
resultProducerTipText() - Method in class weka.experiment.AveragingResultProducer
  Returns the tip text for this property
resultProducerTipText() - Method in class weka.experiment.DatabaseResultProducer
  Returns the tip text for this property
resultProducerTipText() - Method in class weka.experiment.LearningRateResultProducer
  Returns the tip text for this property
resultsetKey() - Method in class weka.experiment.PairedTTester
  Creates a key that maps resultset numbers to their descriptions.
ResultsPanel - Class in weka.gui.experiment
  This panel controls simple analysis of experimental results.
ResultsPanel() - Constructor for class weka.gui.experiment.ResultsPanel
  Creates the results panel with no initial experiment.
retrieveDir() - Method in class weka.core.converters.AbstractFileSaver
  Gets the directory
retrieveDir() - Method in class weka.core.converters.AbstractSaver
  Default implementation throws an IOException.
retrieveDir() - Method in interface weka.core.converters.Saver
  Gets the driectory of the output file This method is used in the KnowledgeFlow GUI.
retrieveFile() - Method in class weka.core.converters.AbstractFileSaver
  Gets the destination file.
retrieveFile() - Method in class weka.core.converters.ArffLoader
  get the File specified as the source
retrieveFile() - Method in class weka.core.converters.C45Loader
  get the File specified as the source
retrieveFile() - Method in class weka.core.converters.CSVLoader
  get the File specified as the source
retrieveFile() - Method in interface weka.core.converters.FileSourcedConverter
  Return the current source file/ destination file
retrieveFile() - Method in class weka.core.converters.SerializedInstancesLoader
  get the File specified as the source
retrieveInstances() - Method in class weka.experiment.InstanceQuery
  Makes a database query using the query set through the -Q option to convert a table into a set of instances
retrieveInstances(String) - Method in class weka.experiment.InstanceQuery
  Makes a database query to convert a table into a set of instances
returnLeaves(FastVector[]) - Method in class weka.classifiers.trees.m5.RuleNode
  Return a list containing all the leaves in the tree
rev() - Method in class weka.classifiers.functions.pace.DoubleVector
  Returns the reverse vector
REVERSED - Static variable in interface weka.gui.graphvisualizer.GraphConstants
  Types of Edges
reversedArcs(BayesNet) - Method in class weka.classifiers.bayes.net.BIFReader
  Count nr of reversed arcs from other network compared to current network
REVISION - Static variable in class weka.core.Version
  the revision
ridgeTipText() - Method in class weka.classifiers.functions.LinearRegression
  Returns the tip text for this property
ridgeTipText() - Method in class weka.classifiers.functions.Logistic
  Returns the tip text for this property
ridgeTipText() - Method in class weka.classifiers.functions.RBFNetwork
  Returns the tip text for this property
Ridor - Class in weka.classifiers.rules
  The implementation of a RIpple-DOwn Rule learner.
Ridor() - Constructor for class weka.classifiers.rules.Ridor
rightNode() - Method in class weka.classifiers.trees.m5.RuleNode
  Get the right child of this node
rightSide(int, Instances) - Method in class weka.classifiers.trees.j48.BinC45Split
  Prints the condition satisfied by instances in a subset.
rightSide(int, Instances) - Method in class weka.classifiers.trees.j48.C45Split
  Prints the condition satisfied by instances in a subset.
rightSide(int, Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
  Prints left side of condition satisfied by instances in subset index.
rightSide(int, Instances) - Method in class weka.classifiers.trees.j48.NBTreeNoSplit
  Does nothing because no condition has to be satisfied.
rightSide(int, Instances) - Method in class weka.classifiers.trees.j48.NBTreeSplit
  Prints the condition satisfied by instances in a subset.
rightSide(int, Instances) - Method in class weka.classifiers.trees.j48.NoSplit
  Does nothing because no condition has to be satisfied.
rightSide(int, Instances) - Method in class weka.classifiers.trees.lmt.ResidualSplit
  Prints the condition satisfied by instances in a subset.
rmCoveredBySuccessives(Instances, FastVector, int) - Static method in class weka.classifiers.rules.RuleStats
  Static utility function to count the data covered by the rules after the given index in the given rules, and then remove them.
rnorm(int, double, double, Random) - Static method in class weka.classifiers.functions.pace.Maths
  Generates a sample of a normal distribution.
rocAnalysisTipText() - Method in class weka.associations.Tertius
  Returns the tip text for this property.
rocToString() - Method in class weka.associations.tertius.Rule
  Return a String giving the TP-rate and FP-rate of this rule.
ROOT_FINDER_ACCURACY - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
ROOT_FINDER_MAX_ITER - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
  How close the root finder for numeric and nominal have to get
ROOT_NODE - Static variable in class weka.core.xml.XMLOptions
  the root node
ROOT_NODE - Static variable in class weka.core.xml.XMLSerialization
  the root node of the XML document
rootMeanPriorSquaredError() - Method in class weka.classifiers.Evaluation
  Returns the root mean prior squared error.
rootMeanSquaredError() - Method in class weka.classifiers.Evaluation
  Returns the root mean squared error.
rootRelativeSquaredError() - Method in class weka.classifiers.Evaluation
  Returns the root relative squared error if the class is numeric.
rotate(double, double, double) - Method in class weka.gui.visualize.PostscriptGraphics
rotate(double) - Method in class weka.gui.visualize.PostscriptGraphics
round(double) - Static method in class weka.core.Utils
  Rounds a double to the next nearest integer value.
roundDouble(double, int) - Static method in class weka.core.Utils
  Rounds a double to the given number of decimal places.
rsolve(PaceMatrix, IntVector, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Solves upper-triangular equation R x = b
RTSI - Class in weka.core
  This utility class is looking for all the classes implementing or inheriting from a given interface or class.
  (RTSI = RunTime Subclass Identification)
RTSI() - Constructor for class weka.core.RTSI
RTSI.StringCompare - Class in weka.core
  compares two strings with the following order:
  case insensitive german umlauts (ä , ö etc.) or other non-ASCII letters are treated as special chars special chars < numbers < letters
RTSI.StringCompare() - Constructor for class weka.core.RTSI.StringCompare
Rule - Class in weka.associations.tertius
  Class representing a rule with a body and a head.
Rule(boolean, int, boolean, boolean, boolean, boolean) - Constructor for class weka.associations.tertius.Rule
  Constructor for a rule when the counter-instances are not stored, giving all the constraints applied to this rule.
Rule(Instances, boolean, int, boolean, boolean, boolean, boolean) - Constructor for class weka.associations.tertius.Rule
  Constructor for a rule when the counter-instances are stored, giving all the constraints applied to this rule.
Rule - Class in weka.classifiers.rules
  Abstract class of generic rule
Rule() - Constructor for class weka.classifiers.rules.Rule
Rule - Class in weka.classifiers.trees.m5
  Generates a single m5 tree or rule
Rule() - Constructor for class weka.classifiers.trees.m5.Rule
  Constructor declaration
RuleGeneration - Class in weka.associations
  Class implementing the rule generation procedure of the predictive apriori algorithm.
RuleGeneration(ItemSet) - Constructor for class weka.associations.RuleGeneration
  Constructor
RuleItem - Class in weka.associations
  Class for storing an (class) association rule.
RuleItem() - Constructor for class weka.associations.RuleItem
  Constructor for an empty RuleItem
RuleItem(RuleItem) - Constructor for class weka.associations.RuleItem
  Constructor that generates a RuleItem out of a given one
RuleItem(ItemSet, ItemSet, int, int, double[], Hashtable) - Constructor for class weka.associations.RuleItem
  Constructor
RuleNode - Class in weka.classifiers.trees.m5
  Constructs a node for use in an m5 tree or rule
RuleNode(double, double, RuleNode) - Constructor for class weka.classifiers.trees.m5.RuleNode
  Creates a new `RuleNode` instance.
RuleStats - Class in weka.classifiers.rules
  This class implements the statistics functions used in the propositional rule learner, from the simpler ones like count of true/false positive/negatives, filter data based on the ruleset, etc.
RuleStats() - Constructor for class weka.classifiers.rules.RuleStats
  Default constructor
RuleStats(Instances, FastVector) - Constructor for class weka.classifiers.rules.RuleStats
  Constructor that provides ruleset and data
run() - Method in class weka.associations.Tertius
  Run the search.
RUN_FIELD_NAME - Static variable in class weka.experiment.CrossValidationResultProducer
RUN_FIELD_NAME - Static variable in class weka.experiment.RandomSplitResultProducer
runCommand(String) - Method in class weka.gui.SimpleCLI
  Executes a simple cli command.
runExperiment() - Method in class weka.experiment.Experiment
  Runs all iterations of the experiment, continuing past errors.
runExperiment() - Method in class weka.experiment.RemoteExperiment
  Overides runExperiment in Experiment
RunNumberPanel - Class in weka.gui.experiment
  This panel controls configuration of lower and upper run numbers in an experiment.
RunNumberPanel() - Constructor for class weka.gui.experiment.RunNumberPanel
  Creates the panel with no initial experiment.
RunNumberPanel(Experiment) - Constructor for class weka.gui.experiment.RunNumberPanel
  Creates the panel with the supplied initial experiment.
RunPanel - Class in weka.gui.experiment
  This panel controls the running of an experiment.
RunPanel() - Constructor for class weka.gui.experiment.RunPanel
  Creates the run panel with no initial experiment.
RunPanel(Experiment) - Constructor for class weka.gui.experiment.RunPanel
  Creates the panel with the supplied initial experiment.
runsTipText() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
runsTipText() - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber
runsTipText() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
runsTipText() - Method in class weka.classifiers.bayes.net.search.global.TabuSearch
runsTipText() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
runsTipText() - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber
runsTipText() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
runsTipText() - Method in class weka.classifiers.bayes.net.search.local.TabuSearch

## S

s_startupListeners - Static variable in class weka.gui.beans.KnowledgeFlowApp
sameClauseAs(Rule) - Method in class weka.associations.tertius.Rule
  Test if this rule and another rule correspond to the same clause.
sameClauseTipText() - Method in class weka.associations.Tertius
  Returns the tip text for this property.
sampeSizePercentTipText() - Method in class weka.filters.supervised.instance.Resample
  Returns the tip text for this property
sampleSizePercentTipText() - Method in class weka.filters.unsupervised.instance.Resample
  Returns the tip text for this property
sampleSizeTipText() - Method in class weka.attributeSelection.ReliefFAttributeEval
  Returns the tip text for this property
sampleSizeTipText() - Method in class weka.classifiers.functions.LeastMedSq
  Returns the tip text for this property
satisfies(Instance) - Method in class weka.associations.tertius.AttributeValueLiteral
satisfies(Instance) - Method in class weka.associations.tertius.Literal
save(StringBuffer) - Method in class weka.gui.SaveBuffer
  Save a buffer
saveBatch() - Method in class weka.gui.beans.Saver
  Saves instances in batch mode
SaveBuffer - Class in weka.gui
  This class handles the saving of StringBuffers to files.
SaveBuffer(Logger, Component) - Constructor for class weka.gui.SaveBuffer
  Constructor
saveComponent() - Method in class weka.gui.visualize.PrintableComponent
  displays a save dialog for saving the panel to a file.
saveComponent() - Method in interface weka.gui.visualize.PrintableHandler
  displays a save dialog for saving the component to a file.
saveComponent() - Method in class weka.gui.visualize.PrintablePanel
  displays a save dialog for saving the panel to a file.
saveFile() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  saves the current data into a file
saveFileAs() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  saves the current data into a new file
saveInstanceDataTipText() - Method in class weka.classifiers.trees.ADTree
saveInstanceDataTipText() - Method in class weka.classifiers.trees.J48
  Returns the tip text for this property
saveInstanceDataTipText() - Method in class weka.clusterers.Cobweb
  Returns the tip text for this property
Saver - Interface in weka.core.converters
  Interface to something that can save Instances to an output destination in some format.
Saver - Class in weka.gui.beans
  Saves data sets using weka.core.converter classes
Saver() - Constructor for class weka.gui.beans.Saver
  Contsructor
SaverBeanInfo - Class in weka.gui.beans
  Bean info class for the saver bean
SaverBeanInfo() - Constructor for class weka.gui.beans.SaverBeanInfo
SaverCustomizer - Class in weka.gui.beans
  GUI Customizer for the saver bean
SaverCustomizer() - Constructor for class weka.gui.beans.SaverCustomizer
  Constructor
saveWeights() - Method in class weka.classifiers.functions.neural.NeuralConnection
  Call this to have the connection save the current weights.
saveWeights() - Method in class weka.classifiers.functions.neural.NeuralNode
  Call this to have the connection save the current weights.
saveWorkingInstancesToFileQ() - Method in class weka.gui.explorer.PreprocessPanel
  Queries the user for a file to save instances as, then saves the instances in a background process.
scale(int) - Method in class weka.gui.beans.BeanVisual
  Reduce this BeanVisual's icon size by the given factor
scale(double, double) - Method in class weka.gui.visualize.PostscriptGraphics
ScatterPlotMatrix - Class in weka.gui.beans
  Bean that encapsulates weka.gui.visualize.MatrixPanel for displaying a scatter plot matrix.
ScatterPlotMatrix() - Constructor for class weka.gui.beans.ScatterPlotMatrix
ScatterPlotMatrixBeanInfo - Class in weka.gui.beans
  Bean info class for the scatter plot matrix bean
ScatterPlotMatrixBeanInfo() - Constructor for class weka.gui.beans.ScatterPlotMatrixBeanInfo
Scoreable - Interface in weka.classifiers.bayes.net.search.local
  Interface for allowing to score a classifier
scoreTypeTipText() - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
scrollToVisible(int, int) - Method in class weka.gui.JTableHelper
  Assumes table is contained in a JScrollPane.
scrollToVisible(JTable, int, int) - Static method in class weka.gui.JTableHelper
  Assumes table is contained in a JScrollPane.
search() - Method in class weka.associations.Tertius
  Search in the space of hypotheses the rules that have the highest confirmation.
search(ASEvaluation, Instances) - Method in class weka.attributeSelection.ASSearch
  Searches the attribute subset/ranking space.
search(ASEvaluation, Instances) - Method in class weka.attributeSelection.BestFirst
  Searches the attribute subset space by best first search
search(ASEvaluation, Instances) - Method in class weka.attributeSelection.ExhaustiveSearch
  Searches the attribute subset space using an exhaustive search.
search(ASEvaluation, Instances) - Method in class weka.attributeSelection.GeneticSearch
  Searches the attribute subset space using a genetic algorithm.
search(ASEvaluation, Instances) - Method in class weka.attributeSelection.GreedyStepwise
  Searches the attribute subset space by forward selection.
search(ASEvaluation, Instances) - Method in class weka.attributeSelection.RaceSearch
  Searches the attribute subset space by racing cross validation errors of competing subsets
search(ASEvaluation, Instances) - Method in class weka.attributeSelection.RandomSearch
  Searches the attribute subset space randomly.
search(ASEvaluation, Instances) - Method in class weka.attributeSelection.Ranker
  Kind of a dummy search algorithm.
search(ASEvaluation, Instances) - Method in class weka.attributeSelection.RankSearch
  Ranks attributes using the specified attribute evaluator and then searches the ranking using the supplied subset evaluator.
search() - Method in class weka.gui.arffviewer.ArffPanel
  searches for a string in the cells
search() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  searches for a string in the cells
search(Vector, String) - Method in class weka.gui.HierarchyPropertyParser
  Helper function to search for the given target string in a given vector in which the elements' value may hopefully is equal to the target.
SearchAlgorithm - Class in weka.classifiers.bayes.net.search
  This is the base class for all search algorithms for learning Bayes networks.
SearchAlgorithm() - Constructor for class weka.classifiers.bayes.net.search.SearchAlgorithm
  c'tor
searchAlgorithmTipText() - Method in class weka.classifiers.bayes.BayesNet
searchBackwardsTipText() - Method in class weka.attributeSelection.GreedyStepwise
  Returns the tip text for this property
SEARCHPATH_ALL - Static variable in class weka.classifiers.trees.ADTree
  The search modes
SEARCHPATH_HEAVIEST - Static variable in class weka.classifiers.trees.ADTree
SEARCHPATH_RANDOM - Static variable in class weka.classifiers.trees.ADTree
SEARCHPATH_ZPURE - Static variable in class weka.classifiers.trees.ADTree
searchPathTipText() - Method in class weka.classifiers.trees.ADTree
searchPercentTipText() - Method in class weka.attributeSelection.RandomSearch
  Returns the tip text for this property
searchPoints(int, int, boolean) - Method in class weka.gui.visualize.Plot2D
  Pops up a window displaying attribute information on any instances at a point+-plotting_point_size (in panel coordinates)
searchTerminationTipText() - Method in class weka.attributeSelection.BestFirst
  Returns the tip text for this property
searchTipText() - Method in class weka.classifiers.meta.AttributeSelectedClassifier
  Returns the tip text for this property
searchTipText() - Method in class weka.filters.supervised.attribute.AttributeSelection
  Returns the tip text for this property
secondInstanceProduced(InstanceEvent) - Method in class weka.gui.streams.InstanceJoiner
secondInstanceProduced(InstanceEvent) - Method in interface weka.gui.streams.SerialInstanceListener
secondValueIndexTipText() - Method in class weka.filters.unsupervised.attribute.SwapValues
secondValueTipText() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues
seedTipText() - Method in class weka.attributeSelection.GeneticSearch
  Returns the tip text for this property
seedTipText() - Method in class weka.attributeSelection.OneRAttributeEval
  Returns a string for this option suitable for display in the gui as a tip text
seedTipText() - Method in class weka.attributeSelection.ReliefFAttributeEval
  Returns the tip text for this property
seedTipText() - Method in class weka.attributeSelection.WrapperSubsetEval
  Returns the tip text for this property
seedTipText() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
seedTipText() - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber
seedTipText() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
seedTipText() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
seedTipText() - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber
seedTipText() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
seedTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
seedTipText() - Method in class weka.classifiers.functions.VotedPerceptron
  Returns the tip text for this property
seedTipText() - Method in class weka.classifiers.functions.Winnow
  Returns the tip text for this property
seedTipText() - Method in class weka.classifiers.meta.MultiScheme
  Returns the tip text for this property
seedTipText() - Method in class weka.classifiers.RandomizableClassifier
  Returns the tip text for this property
seedTipText() - Method in class weka.classifiers.RandomizableIteratedSingleClassifierEnhancer
  Returns the tip text for this property
seedTipText() - Method in class weka.classifiers.RandomizableMultipleClassifiersCombiner
  Returns the tip text for this property
seedTipText() - Method in class weka.classifiers.RandomizableSingleClassifierEnhancer
  Returns the tip text for this property
seedTipText() - Method in class weka.classifiers.rules.ConjunctiveRule
  Returns the tip text for this property
seedTipText() - Method in class weka.classifiers.rules.JRip
  Returns the tip text for this property
seedTipText() - Method in class weka.classifiers.rules.PART
  Returns the tip text for this property
seedTipText() - Method in class weka.classifiers.rules.Ridor
  Returns the tip text for this property
seedTipText() - Method in class weka.classifiers.trees.J48
  Returns the tip text for this property
seedTipText() - Method in class weka.classifiers.trees.RandomForest
  Returns the tip text for this property
seedTipText() - Method in class weka.classifiers.trees.RandomTree
  Returns the tip text for this property
seedTipText() - Method in class weka.classifiers.trees.REPTree
  Returns the tip text for this property
seedTipText() - Method in class weka.clusterers.EM
  Returns the tip text for this property
seedTipText() - Method in class weka.clusterers.FarthestFirst
  Returns the tip text for this property
seedTipText() - Method in class weka.clusterers.SimpleKMeans
  Returns the tip text for this property
seedTipText() - Method in class weka.filters.supervised.attribute.ClassOrder
  Returns the tip text for this property
seedTipText() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds
  Returns the tip text for this property
seedTipText() - Method in class weka.filters.unsupervised.instance.RemoveFolds
  Returns the tip text for this property
seedTipText() - Method in class weka.gui.beans.CrossValidationFoldMaker
  Tip text for this property
seedTipText() - Method in class weka.gui.beans.TrainTestSplitMaker
  Tip text for this property
SelectAttributes(ASEvaluation, String[]) - Static method in class weka.attributeSelection.AttributeSelection
  Perform attribute selection with a particular evaluator and a set of options specifying search method and input file etc.
SelectAttributes(Instances) - Method in class weka.attributeSelection.AttributeSelection
  Perform attribute selection on the supplied training instances.
SelectAttributes(ASEvaluation, String[], Instances) - Static method in class weka.attributeSelection.AttributeSelection
  Perform attribute selection with a particular evaluator and a set of options specifying search method and options for the search method and evaluator.
selectAttributesCVSplit(Instances) - Method in class weka.attributeSelection.AttributeSelection
  Select attributes for a split of the data.
selectedAttributes() - Method in class weka.attributeSelection.AttributeSelection
  get the final selected set of attributes.
SelectedTag - Class in weka.core
  Represents a selected value from a finite set of values, where each value is a Tag (i.e.
SelectedTag(int, Tag[]) - Constructor for class weka.core.SelectedTag
  Creates a new `SelectedTag` instance.
SelectedTagEditor - Class in weka.gui
  A PropertyEditor that uses tags, where the tags are obtained from a weka.core.SelectedTag object.
SelectedTagEditor() - Constructor for class weka.gui.SelectedTagEditor
SELECTION_GREEDY - Static variable in class weka.classifiers.functions.LinearRegression
SELECTION_M5 - Static variable in class weka.classifiers.functions.LinearRegression
SELECTION_NONE - Static variable in class weka.classifiers.functions.LinearRegression
selectionThresholdTipText() - Method in class weka.attributeSelection.RaceSearch
  Returns the tip text for this property
selectModel(Instances) - Method in class weka.classifiers.trees.j48.BinC45ModelSelection
  Selects C4.5-type split for the given dataset.
selectModel(Instances, Instances) - Method in class weka.classifiers.trees.j48.BinC45ModelSelection
  Selects C4.5-type split for the given dataset.
selectModel(Instances) - Method in class weka.classifiers.trees.j48.C45ModelSelection
  Selects C4.5-type split for the given dataset.
selectModel(Instances, Instances) - Method in class weka.classifiers.trees.j48.C45ModelSelection
  Selects C4.5-type split for the given dataset.
selectModel(Instances) - Method in class weka.classifiers.trees.j48.ModelSelection
  Selects a model for the given dataset.
selectModel(Instances, Instances) - Method in class weka.classifiers.trees.j48.ModelSelection
  Selects a model for the given train data using the given test data
selectModel(Instances) - Method in class weka.classifiers.trees.j48.NBTreeModelSelection
  Selects NBTree-type split for the given dataset.
selectModel(Instances, Instances) - Method in class weka.classifiers.trees.j48.NBTreeModelSelection
  Selects NBTree-type split for the given dataset.
selectModel(Instances, double[][], double[][]) - Method in class weka.classifiers.trees.lmt.ResidualModelSelection
  Selects split based on residuals for the given dataset.
selectModel(Instances) - Method in class weka.classifiers.trees.lmt.ResidualModelSelection
  Method not in use
selectModel(Instances, Instances) - Method in class weka.classifiers.trees.lmt.ResidualModelSelection
  Method not in use
SEND_INSTANCES - Static variable in class weka.gui.treevisualizer.TreeDisplayEvent
  Command to remove instances from this node and send them to the VisualizePanel.
separable(DoubleVector, int, int, double) - Method in class weka.classifiers.functions.pace.ChisqMixture
  Return true if a value can be considered for mixture estimatino separately from the data indexed between i0 and i1
separable(DoubleVector, int, int, double) - Method in class weka.classifiers.functions.pace.MixtureDistribution
  Return true if a value can be considered for mixture estimatino separately from the data indexed between i0 and i1
separable(DoubleVector, int, int, double) - Method in class weka.classifiers.functions.pace.NormalMixture
  Return true if a value can be considered for mixture estimatino separately from the data indexed between i0 and i1
seq(int, int) - Static method in class weka.classifiers.functions.pace.IntVector
  Generates an IntVector that stores all integers inclusively between two integers.
SerialInstanceListener - Interface in weka.gui.streams
  Defines an interface for objects able to produce two output streams of instances.
SERIALIZED_OBJ_FILE_EXTENSION - Static variable in class weka.core.Instances
  The filename extension that should be used for bin.
SerializedInstancesLoader - Class in weka.core.converters
  Reads a source that contains serialized Instances.
SerializedInstancesLoader() - Constructor for class weka.core.converters.SerializedInstancesLoader
SerializedInstancesSaver - Class in weka.core.converters
  Serialzes to a destination.
SerializedInstancesSaver() - Constructor for class weka.core.converters.SerializedInstancesSaver
  Constructor
SerializedObject - Class in weka.core
  Class for storing an object in serialized form in memory.
SerializedObject(Object) - Constructor for class weka.core.SerializedObject
  Creates a new serialized object (without compression).
SerializedObject(Object, boolean) - Constructor for class weka.core.SerializedObject
  Creates a new serialized object.
SerialUIDChanger - Class in weka.core.xml
  This class enables one to change the UID of a serialized object and therefore not losing the data stored in the binary format.
SerialUIDChanger() - Constructor for class weka.core.xml.SerialUIDChanger
set(int, double) - Method in class weka.classifiers.functions.pace.DoubleVector
  Set a single element.
set(double) - Method in class weka.classifiers.functions.pace.DoubleVector
  Set all elements to a value
set(int, int, double) - Method in class weka.classifiers.functions.pace.DoubleVector
  Set some elements to a value
set(int, int, double[], int) - Method in class weka.classifiers.functions.pace.DoubleVector
  Set some elements using a 2-D array
set(DoubleVector) - Method in class weka.classifiers.functions.pace.DoubleVector
  Set the elements using a DoubleVector
set(int, int, DoubleVector, int) - Method in class weka.classifiers.functions.pace.DoubleVector
  Set some elements using a DoubleVector.
set(int) - Method in class weka.classifiers.functions.pace.IntVector
  Sets the value of an element.
set(int, int, int[], int) - Method in class weka.classifiers.functions.pace.IntVector
  Sets the values of elements from an int array.
set(int, int, IntVector, int) - Method in class weka.classifiers.functions.pace.IntVector
  Sets the values of elements from another IntVector.
set(IntVector) - Method in class weka.classifiers.functions.pace.IntVector
  Sets the values of elements from another IntVector.
set(int, int) - Method in class weka.classifiers.functions.pace.IntVector
  Sets a single element.
set(int, int, double) - Method in class weka.classifiers.functions.pace.Matrix
  Set a single element.
set(int, int, double) - Method in class weka.core.matrix.Matrix
  Set a single element.
setAcuity(double) - Method in class weka.clusterers.Cobweb
  set the acuity.
setAdditionalMeasures(String[]) - Method in class weka.experiment.AveragingResultProducer
  Set a list of method names for additional measures to look for in SplitEvaluators.
setAdditionalMeasures(String[]) - Method in class weka.experiment.ClassifierSplitEvaluator
  Set a list of method names for additional measures to look for in Classifiers.
setAdditionalMeasures(String[]) - Method in class weka.experiment.CrossValidationResultProducer
  Set a list of method names for additional measures to look for in SplitEvaluators.
setAdditionalMeasures(String[]) - Method in class weka.experiment.DatabaseResultProducer
  Set a list of method names for additional measures to look for in SplitEvaluators.
setAdditionalMeasures(String[]) - Method in class weka.experiment.LearningRateResultProducer
  Set a list of method names for additional measures to look for in SplitEvaluators.
setAdditionalMeasures(String[]) - Method in class weka.experiment.RandomSplitResultProducer
  Set a list of method names for additional measures to look for in SplitEvaluators.
setAdditionalMeasures(String[]) - Method in class weka.experiment.RegressionSplitEvaluator
  Set a list of method names for additional measures to look for in Classifiers.
setAdditionalMeasures(String[]) - Method in interface weka.experiment.ResultProducer
  Sets a list of method names for additional measures to look for in SplitEvaluators.
setAdditionalMeasures(String[]) - Method in interface weka.experiment.SplitEvaluator
  Sets a list of method names for additional measures to look for in SplitEvaluators.
setAdjustWeights(boolean) - Method in class weka.filters.supervised.instance.SpreadSubsample
  Sets whether the instance weights will be adjusted to maintain total weight per class.
setAdvanceDataSetFirst(boolean) - Method in class weka.experiment.Experiment
  Set the value of m_AdvanceDataSetFirst.
setAlpha(double) - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator
  Set prior used in probability table estimation
setAlpha(double) - Method in class weka.classifiers.functions.Winnow
  Set the value of Alpha.
setAnimated() - Method in class weka.gui.beans.BeanVisual
  Set the animated version of the icon
setAppendPredictedProbabilities(boolean) - Method in class weka.gui.beans.PredictionAppender
  Set whether to append predicted probabilities rather than class value (for discrete class data sets)
setArffFile(String) - Method in class weka.gui.streams.InstanceLoader
setArffFile(String) - Method in class weka.gui.streams.InstanceSavePanel
setArtificialSize(double) - Method in class weka.classifiers.meta.Decorate
  Sets factor that determines number of artificial examples to generate.
setAssociatedConnections(Vector) - Method in class weka.gui.beans.MetaBean
setAsText(String) - Method in class weka.gui.CostMatrixEditor
  Some objects can be represented as text, but a cost matrix cannot.
setAsText(String) - Method in class weka.gui.GenericArrayEditor
  Returns null as we don't support getting/setting values as text.
setAsText(String) - Method in class weka.gui.GenericObjectEditor
  Returns null as we don't support getting/setting values as text.
setAsText(String) - Method in class weka.gui.SelectedTagEditor
  Sets the current property value as text.
setAsText(String) - Method in class weka.gui.SimpleDateFormatEditor
  Sets the date format string.
setAttIndex(int, boolean) - Method in class weka.classifiers.lazy.LBR.Indexes
  Changes the boolean value at the specified index in the AttIndexes array
setAttList_Irr(boolean[]) - Method in class weka.datagenerators.RDG1
  Sets the array that defines which of the attributes are seen to be irrelevant.
setAttribute(int) - Method in class weka.gui.AttributeSummaryPanel
  Sets the attribute that statistics will be displayed for.
setAttribute(int) - Method in class weka.gui.AttributeVisualizationPanel
  Tells the panel which attribute to visualize.
setAttributeEvaluator(ASEvaluation) - Method in class weka.attributeSelection.RaceSearch
  Set the attribute evaluator to use for generating the ranking.
setAttributeEvaluator(ASEvaluation) - Method in class weka.attributeSelection.RankSearch
  Set the attribute evaluator to use for generating the ranking.
setAttributeID(int) - Method in class weka.experiment.ClassifierSplitEvaluator
  Set the index of Attibute Identifying the instances
setAttributeIndex(String) - Method in class weka.filters.unsupervised.attribute.Add
  Sets index of the attribute used.
setAttributeIndex(String) - Method in class weka.filters.unsupervised.attribute.AddNoise
  Sets index of the attribute used.
setAttributeIndex(String) - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat
  Sets the index of the attribute used.
setAttributeIndex(String) - Method in class weka.filters.unsupervised.attribute.MakeIndicator
  Sets index of the attribute used.
setAttributeIndex(String) - Method in class weka.filters.unsupervised.attribute.MergeTwoValues
  Sets index of the attribute used.
setAttributeIndex(String) - Method in class weka.filters.unsupervised.attribute.StringToNominal
  Sets index of the attribute used.
setAttributeIndex(String) - Method in class weka.filters.unsupervised.attribute.SwapValues
  Sets index of the attribute used.
setAttributeIndex(String) - Method in class weka.filters.unsupervised.instance.RemoveWithValues
  Sets index of the attribute used.
setAttributeIndices(String) - Method in class weka.filters.supervised.attribute.Discretize
  Sets which attributes are to be Discretized (only numeric attributes among the selection will be Discretized).
setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries
  Set which attributes are to be copied (or kept if invert is true)
setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.Copy
  Set which attributes are to be copied (or kept if invert is true)
setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.Discretize
  Sets which attributes are to be Discretized (only numeric attributes among the selection will be Discretized).
setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.FirstOrder
  Set which attributes are to be deleted (or kept if invert is true)
setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.NominalToBinary
  Sets which attributes are to be acted on.
setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.NumericTransform
  Set which attributes are to be transformed (or kept if invert is true).
setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.Remove
  Set which attributes are to be deleted (or kept if invert is true)
setAttributeIndicesArray(int[]) - Method in class weka.filters.supervised.attribute.Discretize
  Sets which attributes are to be Discretized (only numeric attributes among the selection will be Discretized).
setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries
  Set which attributes are to be copied (or kept if invert is true)
setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.Copy
  Set which attributes are to be copied (or kept if invert is true)
setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.Discretize
  Sets which attributes are to be Discretized (only numeric attributes among the selection will be Discretized).
setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.FirstOrder
  Set which attributes are to be deleted (or kept if invert is true)
setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.NumericTransform
  Set which attributes are to be transformed (or kept if invert is true)
setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.Remove
  Set which attributes are to be deleted (or kept if invert is true)
setAttributeName(String) - Method in class weka.filters.unsupervised.attribute.Add
  Set the new attribute's name
setAttributeNamePrefix(String) - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Set the attribute name prefix.
setAttributeSelectionMethod(SelectedTag) - Method in class weka.classifiers.functions.LinearRegression
  Sets the method used to select attributes for use in the linear regression.
setAttributeType(SelectedTag) - Method in class weka.filters.unsupervised.attribute.RemoveType
  Sets the attribute type to be deleted by the filter.
setAtts(int[], boolean) - Method in class weka.classifiers.lazy.LBR.Indexes
  Changes the boolean value at the specified index in the InstIndexes array
setAttsToEliminatePerIteration(int) - Method in class weka.attributeSelection.SVMAttributeEval
  Set the constant rate of attribute elimination per iteration
setAutoBuild(boolean) - Method in class weka.classifiers.functions.MultilayerPerceptron
  This will set whether the network is automatically built or if it is left up to the user.
setAutoKeyGeneration(boolean) - Method in class weka.core.converters.DatabaseSaver
  En/Dis-ables the automatic generation of a primary key
setBackground(Color) - Method in class weka.gui.visualize.JPEGWriter
  sets the background color to use in creating the JPEG
setBackground(Color) - Method in class weka.gui.visualize.PostscriptGraphics
setBagSizePercent(int) - Method in class weka.classifiers.meta.Bagging
  Sets the size of each bag, as a percentage of the training set size.
setBagSizePercent(int) - Method in class weka.classifiers.meta.MetaCost
  Sets the size of each bag, as a percentage of the training set size.
setBalanced(boolean) - Method in class weka.classifiers.functions.Winnow
  Set the value of Balanced.
setBaseExperiment(Experiment) - Method in class weka.experiment.RemoteExperiment
  Set the base experiment.
setBeanContext(BeanContext) - Method in class weka.gui.beans.AbstractDataSource
  Set a bean context for this bean
setBeanContext(BeanContext) - Method in class weka.gui.beans.AttributeSummarizer
  Set a bean context for this bean
setBeanContext(BeanContext) - Method in class weka.gui.beans.DataVisualizer
  Set a bean context for this bean
setBeanContext(BeanContext) - Method in class weka.gui.beans.Loader
  Set a bean context for this bean
setBeanContext(BeanContext) - Method in class weka.gui.beans.ModelPerformanceChart
  Set a bean context for this bean
setBeanContext(BeanContext) - Method in class weka.gui.beans.TextViewer
  Set a bean context for this bean
setBeanInstances(Vector, JComponent) - Static method in class weka.gui.beans.BeanInstance
  Describe `setBeanInstances` method here.
setBeta(double) - Method in class weka.classifiers.functions.Winnow
  Set the value of Beta.
setBias(double) - Method in class weka.classifiers.misc.VFI
  Set the value of the exponential bias towards more confident intervals
setBiasToUniformClass(double) - Method in class weka.filters.supervised.instance.Resample
  Sets the bias towards a uniform class.
setBIFFile(String) - Method in class weka.classifiers.bayes.BayesNet
  Set name of network in BIF file to compare with
setBIFFile(String) - Method in class weka.classifiers.bayes.net.search.fixed.FromFile
  Set name of network in BIF file to read structure from
setBinarizeNumericAttributes(boolean) - Method in class weka.attributeSelection.ChiSquaredAttributeEval
  Binarize numeric attributes.
setBinarizeNumericAttributes(boolean) - Method in class weka.attributeSelection.InfoGainAttributeEval
  Binarize numeric attributes.
setBinaryAttributesNominal(boolean) - Method in class weka.filters.supervised.attribute.NominalToBinary
  Sets if binary attributes are to be treates as nominal ones.
setBinaryAttributesNominal(boolean) - Method in class weka.filters.unsupervised.attribute.NominalToBinary
  Sets if binary attributes are to be treates as nominal ones.
setBinarySplits(boolean) - Method in class weka.classifiers.rules.PART
  Set the value of binarySplits.
setBinarySplits(boolean) - Method in class weka.classifiers.trees.J48
  Set the value of binarySplits.
setBins(int) - Method in class weka.filters.unsupervised.attribute.Discretize
  Sets the number of bins to divide each selected numeric attribute into
setBins(int) - Method in class weka.filters.unsupervised.attribute.PKIDiscretize
  Ignored
setBlendFactor(int) - Method in class weka.classifiers.lazy.kstar.KStarNumericAttribute
  Set the blending factor
setBlendMethod(int) - Method in class weka.classifiers.lazy.kstar.KStarNumericAttribute
  Set the blending method
setBuildLogisticModels(boolean) - Method in class weka.classifiers.functions.SMO
  Set the value of buildLogisticModels.
setBuildRegressionTree(boolean) - Method in class weka.classifiers.trees.m5.M5Base
  Set the value of regressionTree.
setC(double) - Method in class weka.classifiers.functions.SMO
  Set the value of C.
setC(double) - Method in class weka.classifiers.functions.SMOreg
  Set the value of C.
setCacheKeyName(String) - Method in class weka.experiment.DatabaseResultListener
  Set the value of CacheKeyName.
setCacheSize(int) - Method in class weka.classifiers.functions.SMO
  Set the value of the kernel cache.
setCacheSize(int) - Method in class weka.classifiers.functions.SMOreg
  Set the value of the kernel cache.
setCalcOutOfBag(boolean) - Method in class weka.classifiers.meta.Bagging
  Set whether the out of bag error is calculated.
setCalculateStdDevs(boolean) - Method in class weka.experiment.AveragingResultProducer
  Set the value of CalculateStdDevs.
setCapacity(int) - Method in class weka.classifiers.functions.pace.DoubleVector
  Sets the capacity of the vector
setCapacity(int) - Method in class weka.classifiers.functions.pace.IntVector
  Sets the capacity of the vector
setCapacity(int) - Method in class weka.core.FastVector
  Sets the vector's capacity to the given value.
setCenter(double) - Method in class weka.gui.treevisualizer.Node
  Set the value of center.
setCenteredLocation() - Method in class weka.gui.arffviewer.ArffViewer
  positions the window at the center of the screen
setChanged(boolean) - Method in class weka.gui.arffviewer.ArffPanel
  can only reset the changed state to FALSE
setCheckErrorRate(boolean) - Method in class weka.classifiers.rules.JRip
setChildForBranch(int, PredictionNode) - Method in class weka.classifiers.trees.adtree.Splitter
  Sets the child for a branch of the split.
setChildForBranch(int, PredictionNode) - Method in class weka.classifiers.trees.adtree.TwoWayNominalSplit
  Sets the child for a branch of the split.
setChildForBranch(int, PredictionNode) - Method in class weka.classifiers.trees.adtree.TwoWayNumericSplit
  Sets the child for a branch of the split.
setCindex(int, double, double) - Method in class weka.gui.visualize.AttributePanel
  Set the index of the attribute by which to colour the data.
setCindex(int) - Method in class weka.gui.visualize.AttributePanel
  Set the index of the attribute by which to colour the data.
setCindex(int) - Method in class weka.gui.visualize.ClassPanel
  Set the index of the attribute to display coloured labels for
setCindex(int) - Method in class weka.gui.visualize.Plot2D
  Set the index of the attribute to use for colouring
setCindex(int) - Method in class weka.gui.visualize.PlotData2D
  Set the colouring index of the data
setClass(Attribute) - Method in class weka.core.Instances
  Sets the class attribute.
setClassColumn(String) - Method in class weka.gui.beans.ClassAssigner
setClassFlag(boolean) - Method in class weka.datagenerators.ClusterGenerator
  Sets the class flag, if class flag is set, the cluster is listed as class atrribute in an extra attribute.
setClassForIRStatistics(int) - Method in class weka.experiment.ClassifierSplitEvaluator
  Set the value of ClassForIRStatistics.
setClassification(boolean) - Method in class weka.associations.Tertius
  Set the value of classification.
setClassifier(Classifier) - Method in class weka.attributeSelection.ClassifierSubsetEval
  Set the classifier to use for accuracy estimation
setClassifier(Classifier) - Method in class weka.attributeSelection.WrapperSubsetEval
  Set the classifier to use for accuracy estimation
setClassifier(Classifier) - Method in class weka.classifiers.BVDecompose
  Set the classifiers being analysed
setClassifier(Classifier) - Method in class weka.classifiers.BVDecomposeSegCVSub
  Set the classifiers being analysed
setClassifier(Classifier) - Method in class weka.classifiers.CheckClassifier
  Set the classifier for boosting.
setClassifier(Classifier) - Method in class weka.classifiers.SingleClassifierEnhancer
  Set the base learner.
setClassifier(Classifier) - Method in class weka.experiment.ClassifierSplitEvaluator
  Sets the classifier.
setClassifier(Classifier) - Method in class weka.experiment.RegressionSplitEvaluator
  Sets the classifier.
setClassifier(Classifier) - Method in class weka.filters.unsupervised.instance.RemoveMisclassified
  Sets the classifier to classify instances with.
setClassifier(Classifier) - Method in class weka.gui.beans.Classifier
  Set the classifier for this wrapper
setClassifier(Classifier) - Method in class weka.gui.beans.IncrementalClassifierEvent
setClassifier(Classifier) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel
  Set the classifier to use.
setClassifier(Classifier) - Method in class weka.gui.boundaryvisualizer.BoundaryVisualizer
  Set a classifier to use
setClassifier(Classifier) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
  Set the classifier to use
setClassifierName(String) - Method in class weka.experiment.ClassifierSplitEvaluator
  Set the Classifier to use, given it's class name.
setClassifierName(String) - Method in class weka.experiment.RegressionSplitEvaluator
  Set the Classifier to use, given it's class name.
setClassifiers(Classifier[]) - Method in class weka.classifiers.meta.MultiScheme
  Sets the list of possible classifers to choose from.
setClassifiers(Classifier[]) - Method in class weka.classifiers.MultipleClassifiersCombiner
  Sets the list of possible classifers to choose from.
setClassifyIterations(int) - Method in class weka.classifiers.BVDecomposeSegCVSub
  Sets the number of times an instance is classified
setClassIndex(int) - Method in class weka.associations.Tertius
  Set the value of classIndex.
setClassIndex(int) - Method in class weka.classifiers.BVDecompose
  Sets index of attribute to discretize on
setClassIndex(int) - Method in class weka.classifiers.BVDecomposeSegCVSub
  Sets index of attribute to discretize on
setClassIndex(int) - Method in class weka.core.Instances
  Sets the class index of the set.
setClassIndex(int) - Method in class weka.filters.unsupervised.instance.RemoveMisclassified
  Sets the attribute on which misclassifications are based.
setClassMissing() - Method in class weka.core.Instance
  Sets the class value of an instance to be "missing".
setClassName(String) - Method in class weka.filters.unsupervised.attribute.NumericTransform
  Sets the class containing the transformation method.
setClassOrder(int) - Method in class weka.filters.supervised.attribute.ClassOrder
  Set the wanted class order
setClassType(Class) - Method in class weka.gui.GenericObjectEditor
  Sets the class of values that can be edited.
setClassValue(double) - Method in class weka.core.Instance
  Sets the class value of an instance to the given value (internal floating-point format).
setClassValue(String) - Method in class weka.core.Instance
  Sets the class value of an instance to the given value.
setClassValueIndex(int) - Method in class weka.gui.beans.ClassValuePicker
  Set the class value index considered to be the "positive" class value.
setClearEachDataset(boolean) - Method in class weka.gui.streams.InstanceViewer
setClip(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
  Not implemented
setClip(Shape) - Method in class weka.gui.visualize.PostscriptGraphics
  Not implemented
setClusterer(Clusterer) - Method in class weka.clusterers.ClusterEvaluation
  set the clusterer
setClusterer(Clusterer) - Method in class weka.clusterers.MakeDensityBasedClusterer
  Sets the clusterer to wrap.
setClusterer(Clusterer) - Method in class weka.filters.unsupervised.attribute.AddCluster
  Sets the clusterer to assign clusters with.
setClusterer(Clusterer) - Method in class weka.gui.beans.Clusterer
  Set the clusterer for this wrapper
setClusteringSeed(int) - Method in class weka.classifiers.functions.RBFNetwork
  Set the random seed to be passed on to K-means.
setColor(Color) - Method in class weka.gui.treevisualizer.Node
  Set the value of color.
setColor(Color) - Method in class weka.gui.visualize.PostscriptGraphics
  Set current pen color.
setColoringIndex(int) - Method in class weka.gui.AttributeVisualizationPanel
  Set the coloring (class) index for the plot
setColoringIndex(int) - Method in class weka.gui.beans.AttributeSummarizer
  Set the coloring index for the attribute summary plots
setColors(FastVector) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel
  Set a vector of Color objects for the classes
setColourIndex(int) - Method in class weka.gui.visualize.VisualizePanel
  Sets the index used for colouring.
setColours(FastVector) - Method in class weka.gui.visualize.AttributePanel
  Sets a list of colours to use for colouring data points
setColours(FastVector) - Method in class weka.gui.visualize.ClassPanel
  Set a list of colours to use for colouring labels
setColours(FastVector) - Method in class weka.gui.visualize.Plot2D
  Set a list of colours to use when colouring points according to class values or cluster numbers
setColumn(int, double[]) - Method in class weka.core.Matrix
  Deprecated. Sets a column of the matrix to the given column.
setColumnDimension(int) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Set the column dimenion of the matrix
setComplexityParameter(double) - Method in class weka.attributeSelection.SVMAttributeEval
  Set the value of C for SMO
setComponent(JComponent) - Method in class weka.gui.visualize.JComponentWriter
  sets the component to print to an output format
setComposite(Composite) - Method in class weka.gui.visualize.PostscriptGraphics
setConfidenceFactor(float) - Method in class weka.classifiers.rules.PART
  Set the value of CF.
setConfidenceFactor(float) - Method in class weka.classifiers.trees.J48
  Set the value of CF.
setConfirmationThreshold(double) - Method in class weka.associations.Tertius
  Set the value of confirmationThreshold.
setConfirmationValues(int) - Method in class weka.associations.Tertius
  Set the value of confirmationValues.
setConfirmExit(boolean) - Method in class weka.gui.arffviewer.ArffViewer
  whether to present a MessageBox on Exit or not
setConfirmExit(boolean) - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  whether to present a MessageBox on Exit or not
setConnections(Vector) - Static method in class weka.gui.beans.BeanConnection
  Describe `setConnections` method here.
setConnectPoints(boolean[]) - Method in class weka.gui.visualize.PlotData2D
  Set whether consecutive points should be connected by lines
setConnectPoints(FastVector) - Method in class weka.gui.visualize.PlotData2D
  Set whether consecutive points should be connected by lines
setConvertNominal(boolean) - Method in class weka.classifiers.trees.LMT
  Set the value of convertNominal.
setCostMatrix(CostMatrix) - Method in class weka.classifiers.meta.CostSensitiveClassifier
  Sets the misclassification cost matrix.
setCostMatrix(CostMatrix) - Method in class weka.classifiers.meta.MetaCost
  Sets the misclassification cost matrix.
setCostMatrixSource(SelectedTag) - Method in class weka.classifiers.meta.CostSensitiveClassifier
  Sets the source location of the cost matrix.
setCostMatrixSource(SelectedTag) - Method in class weka.classifiers.meta.MetaCost
  Sets the source location of the cost matrix.
setCounter(int) - Method in class weka.associations.ItemSet
  Sets the counter
setCrossoverProb(double) - Method in class weka.attributeSelection.GeneticSearch
  set the probability of crossover
setCrossVal(int) - Method in class weka.classifiers.rules.DecisionTable
  Sets the number of folds for cross validation (1 = leave one out)
setCrossValidate(boolean) - Method in class weka.classifiers.lazy.IBk
  Sets whether hold-one-out cross-validation will be used to select the best k value
setCurrentFilename(String) - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  sets the filename of the current tab
setCurrentInstance(Instance) - Method in class weka.gui.beans.IncrementalClassifierEvent
  Set the current instance for this event
setCustomColour(Color) - Method in class weka.gui.visualize.PlotData2D
  Set a custom colour to use for this plot.
setCutoff(double) - Method in class weka.clusterers.Cobweb
  set the cutoff
setCVisible(boolean) - Method in class weka.gui.treevisualizer.Node
  Sets all the children of this node either to visible or invisible
setCVParameters(Object[]) - Method in class weka.classifiers.meta.CVParameterSelection
  Set method for CVParameters.
setCVType(SelectedTag) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
  set cross validation strategy to be used in searching for networks.
setData(Instances) - Method in class weka.classifiers.rules.RuleStats
  Set the data of the stats, overwriting the old one if any
setDatabaseURL(String) - Method in class weka.experiment.DatabaseUtils
  Set the value of DatabaseURL.
setDataFileName(String) - Method in class weka.classifiers.BVDecompose
  Sets the maximum number of boost iterations
setDataFileName(String) - Method in class weka.classifiers.BVDecomposeSegCVSub
  Sets the name of the dataset file.
setDataGenerator(DataGenerator) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel
  Set the data generator to use for generating new instances
setDataGenerator(DataGenerator) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
  Set the density estimator to use
setDataPoint(double[]) - Method in class weka.gui.beans.ChartEvent
  Set the data point
setDataset(Instances) - Method in class weka.core.Instance
  Sets the reference to the dataset.
setDatasetFormat(Instances) - Method in class weka.datagenerators.BIRCHCluster
  Sets the dataset format.
setDatasetFormat(Instances) - Method in class weka.datagenerators.RDG1
  Sets the dataset format.
setDatasetKeyColumns(Range) - Method in class weka.experiment.PairedTTester
  Set the value of DatasetKeyColumns.
setDatasetKeyFromDialog() - Method in class weka.gui.experiment.ResultsPanel
setDatasets(DefaultListModel) - Method in class weka.experiment.Experiment
  Set the datasets to use in the experiment
setDatasets(DefaultListModel) - Method in class weka.experiment.RemoteExperiment
  Set the datasets to use in the experiment
setDataType(int) - Method in class weka.gui.beans.xml.XMLBeans
  sets what kind of data is to be read/written
setDateFormat(String) - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat
  Sets the output date format.
setDateFormat(SimpleDateFormat) - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat
  Sets the output date format.
setDB(boolean) - Method in class weka.gui.beans.Loader
setDebug(boolean) - Method in class weka.attributeSelection.RaceSearch
  Set whether verbose output should be generated.
setDebug(boolean) - Method in class weka.classifiers.BVDecompose
  Sets debugging mode
setDebug(boolean) - Method in class weka.classifiers.BVDecomposeSegCVSub
  Sets debugging mode
setDebug(boolean) - Method in class weka.classifiers.CheckClassifier
  Set debugging mode
setDebug(boolean) - Method in class weka.classifiers.Classifier
  Set debugging mode.
setDebug(boolean) - Method in class weka.classifiers.functions.LeastMedSq
  sets whether or not debugging output shouild be printed
setDebug(boolean) - Method in class weka.classifiers.functions.LinearRegression
  Controls whether debugging output will be printed
setDebug(boolean) - Method in class weka.classifiers.functions.Logistic
  Sets whether debugging output will be printed.
setDebug(boolean) - Method in class weka.classifiers.functions.PaceRegression
  Controls whether debugging output will be printed
setDebug(boolean) - Method in class weka.classifiers.meta.MultiScheme
  Set debugging mode
setDebug(boolean) - Method in class weka.classifiers.rules.JRip
setDebug(boolean) - Method in class weka.classifiers.trees.RandomTree
  Set the value of Debug.
setDebug(boolean) - Method in class weka.clusterers.EM
  Set debug mode - verbose output
setDebug(boolean) - Method in class weka.core.Optimization
  Set whether in debug mode
setDebug(boolean) - Method in class weka.datagenerators.ClusterGenerator
  Sets the debug flag.
setDebug(boolean) - Method in class weka.datagenerators.Generator
  Sets the debug flag.
setDebug(boolean) - Method in class weka.experiment.DatabaseUtils
  Sets whether there should be printed some debugging output to stderr or not
setDebug(boolean) - Method in class weka.filters.unsupervised.attribute.AddExpression
  Set debug mode.
setDebug(boolean) - Method in class weka.gui.streams.InstanceCounter
setDebug(boolean) - Method in class weka.gui.streams.InstanceJoiner
setDebug(boolean) - Method in class weka.gui.streams.InstanceLoader
setDebug(boolean) - Method in class weka.gui.streams.InstanceSavePanel
setDebug(boolean) - Method in class weka.gui.streams.InstanceTable
setDebug(boolean) - Method in class weka.gui.streams.InstanceViewer
setDecay(boolean) - Method in class weka.classifiers.functions.MultilayerPerceptron
setDefaultOptions() - Method in class weka.datagenerators.BIRCHCluster
  Sets all options to their default values.
setDefaultValue() - Method in class weka.gui.GenericObjectEditor
  Sets the current object to be the default, taken as the first item in the chooser
setDefaultWeight(double) - Method in class weka.classifiers.functions.Winnow
  Set the value of defaultWeight.
setDelimiters(String) - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Set the value of delimiters.
setDelta(double) - Method in class weka.associations.Apriori
  Set the value of delta.
setDelta(double) - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
  Sets the m_fDelta.
setDelta(double) - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
  Sets the m_fDelta.
setDensityBasedClusterer(DensityBasedClusterer) - Method in class weka.filters.unsupervised.attribute.ClusterMembership
  Set the clusterer for use in filtering
setDescendantPopulationSize(int) - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
setDescendantPopulationSize(int) - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
setDesign(boolean) - Method in class weka.gui.beans.AttributeSummarizer
  Set whether the appearance of this bean should be design or application
setDesignatedClass(SelectedTag) - Method in class weka.classifiers.meta.ThresholdSelector
  Sets the method to determine which class value to optimize.
setDesiredSize(int) - Method in class weka.classifiers.meta.Decorate
  Sets the desired size of the committee.
setDesiredWeightOfInstancesPerInterval(double) - Method in class weka.filters.unsupervised.attribute.Discretize
  Set the DesiredWeightOfInstancesPerInterval value.
setDestination(File) - Method in class weka.core.converters.AbstractFileSaver
  Sets the destination file (and directories if necessary).
setDestination(OutputStream) - Method in class weka.core.converters.AbstractFileSaver
  Sets the destination output stream.
setDestination(File) - Method in class weka.core.converters.AbstractSaver
  Default implementation throws an IOException.
setDestination(OutputStream) - Method in class weka.core.converters.AbstractSaver
  Default implementation throws an IOException.
setDestination(String, String, String) - Method in class weka.core.converters.DatabaseSaver
  Sets the database url
setDestination(String) - Method in class weka.core.converters.DatabaseSaver
  Sets the database url
setDestination() - Method in class weka.core.converters.DatabaseSaver
  Sets the database url using the DatabaseUtils file
setDestination(File) - Method in interface weka.core.converters.Saver
  Resets the Saver object and sets the destination to be the supplied File object.
setDestination(OutputStream) - Method in interface weka.core.converters.Saver
  Resets the Saver object and sets the destination to be the supplied InputStream.
setDestination(File) - Method in class weka.core.converters.SerializedInstancesSaver
  Sets the destination file (and directories if necessary).
setDir(String) - Method in class weka.core.converters.AbstractFileSaver
  Sets the directory where the instances should be stored
setDir(String) - Method in class weka.core.converters.AbstractSaver
  Default implementation throws an IOException.
setDir(String) - Method in interface weka.core.converters.Saver
  Sets the directory of the output file.
setDirAndPrefix(String, String) - Method in class weka.core.converters.AbstractFileSaver
  Sets the directory and the file prefix.
setDirAndPrefix(String, String) - Method in class weka.core.converters.AbstractSaver
  Default implementation throws an IOException.
setDirAndPrefix(String, String) - Method in interface weka.core.converters.Saver
  Sets the file prefix and the directory.
setDirection(SelectedTag) - Method in class weka.attributeSelection.BestFirst
  Set the search direction
setDisplayConnectors(boolean) - Method in class weka.gui.beans.BeanVisual
  Turn on/off the connector points
setDisplayConnectors(boolean, Color) - Method in class weka.gui.beans.BeanVisual
  Turn on/off the connector points
setDisplayedFromDialog() - Method in class weka.gui.experiment.ResultsPanel
setDisplayedResultsets(int[]) - Method in class weka.experiment.PairedTTester
  Sets the indicies of the datasets to display (`null` means all).
setDisplayRules(boolean) - Method in class weka.classifiers.rules.DecisionTable
  Sets whether rules are to be printed
setDistanceWeighting(SelectedTag) - Method in class weka.classifiers.lazy.IBk
  Sets the distance weighting method used.
setDistMult(double) - Method in class weka.datagenerators.BIRCHCluster
  Sets the distance multiplier.
setDistribution(SelectedTag) - Method in class weka.filters.unsupervised.attribute.RandomProjection
  Sets the distribution to use for calculating the random matrix
setDistributionSpread(double) - Method in class weka.filters.supervised.instance.SpreadSubsample
  Sets the value for the distribution spread
setDocType(String) - Method in class weka.core.xml.XMLDocument
  sets the DOCTYPE-String to use in the XML output.
setDocument(Document) - Method in class weka.core.xml.XMLDocument
  sets the DOM document to use
setDontNormalize(boolean) - Method in class weka.classifiers.lazy.LWL
  Sets whether if the numeric attribute values are not to be normalized for calculating the distances between them.
setElement(int, int, double) - Method in class weka.core.Matrix
  Deprecated. Sets an element of the matrix to the given value.
setElementAt(Object, int) - Method in class weka.core.FastVector
  Sets the element at the given index.
setEliminateColinearAttributes(boolean) - Method in class weka.classifiers.functions.LinearRegression
  Set the value of EliminateColinearAttributes.
setEnabled(boolean) - Method in class weka.core.Memory
  sets whether the memory management is enabled
setEnabled(boolean) - Method in class weka.gui.GenericObjectEditor
  Sets whether the editor is "enabled", meaning that the current values will be painted.
setEntropicAutoBlend(boolean) - Method in class weka.classifiers.lazy.KStar
  Set whether entropic blending is to be used.
setEps(double) - Method in class weka.classifiers.functions.SMOreg
  Set the value of eps.
setEpsilon(double) - Method in class weka.classifiers.functions.SMO
  Set the value of epsilon.
setEpsilon(double) - Method in class weka.classifiers.functions.SMOreg
  Set the value of epsilon.
setEpsilonParameter(double) - Method in class weka.attributeSelection.SVMAttributeEval
  Set the value of P for SMO
setErrorOnProbabilities(boolean) - Method in class weka.classifiers.functions.SimpleLogistic
  Set the value of errorOnProbabilities.
setErrorOnProbabilities(boolean) - Method in class weka.classifiers.trees.LMT
  Set the value of errorOnProbabilities.
setEstimator(BayesNetEstimator) - Method in class weka.classifiers.bayes.BayesNet
  Set the Estimator Algorithm used in calculating the CPTs
setEstimator(SelectedTag) - Method in class weka.classifiers.functions.PaceRegression
  Sets the estimator.
setEvaluationMode(SelectedTag) - Method in class weka.classifiers.meta.ThresholdSelector
  Sets the evaluation mode used.
setEvaluator(ASEvaluation) - Method in class weka.attributeSelection.AttributeSelection
  set the attribute/subset evaluator
setEvaluator(ASEvaluation) - Method in class weka.classifiers.meta.AttributeSelectedClassifier
  Sets the attribute evaluator
setEvaluator(ASEvaluation) - Method in class weka.filters.supervised.attribute.AttributeSelection
  set a string holding the name of a attribute/subset evaluator
setEvalUsingTrainingData(boolean) - Method in class weka.attributeSelection.OneRAttributeEval
  Use the training data to evaluate attributes rather than cross validation
setExclusive(boolean) - Method in class weka.classifiers.rules.ConjunctiveRule
setExecutionStatus(int) - Method in class weka.experiment.TaskStatusInfo
  Set the execution status of this Task.
setExitOnClose(boolean) - Method in class weka.gui.arffviewer.ArffViewer
  whether to do a System.exit(0) on close
setExitOnClose(boolean) - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  whether to do a System.exit(0) on close
setExpectedResultsPerAverage(int) - Method in class weka.experiment.AveragingResultProducer
  Set the value of ExpectedResultsPerAverage.
setExperiment(Experiment) - Method in class weka.experiment.RemoteExperimentSubTask
  Set the experiment for this sub task
setExperiment(Experiment) - Method in class weka.gui.experiment.AlgorithmListPanel
  Tells the panel to act on a new experiment.
setExperiment(Experiment) - Method in class weka.gui.experiment.DatasetListPanel
  Tells the panel to act on a new experiment.
setExperiment(Experiment) - Method in class weka.gui.experiment.DistributeExperimentPanel
  Sets the experiment to be configured.
setExperiment(Experiment) - Method in class weka.gui.experiment.GeneratorPropertyIteratorPanel
  Sets the experiment which will have the custom properties edited.
setExperiment(RemoteExperiment) - Method in class weka.gui.experiment.HostListPanel
  Tells the panel to act on a new experiment.
setExperiment(Experiment) - Method in class weka.gui.experiment.ResultsPanel
  Tells the panel to use a new experiment.
setExperiment(Experiment) - Method in class weka.gui.experiment.RunNumberPanel
  Sets the experiment to be configured.
setExperiment(Experiment) - Method in class weka.gui.experiment.RunPanel
  Sets the experiment the panel operates on.
setExperiment(Experiment) - Method in class weka.gui.experiment.SetupPanel
  Sets the experiment to configure.
setExperiment(Experiment) - Method in class weka.gui.experiment.SimpleSetupPanel
  Sets the experiment to configure.
setExplicitPropsFile(boolean) - Method in class weka.gui.GenericPropertiesCreator
  if FALSE, the locating of a props-file of the Utils-class is used, otherwise it's tried to load the specified file
setExponent(double) - Method in class weka.classifiers.functions.SMO
  Set the value of exponent.
setExponent(double) - Method in class weka.classifiers.functions.SMOreg
  Set the value of exponent.
setExponent(double) - Method in class weka.classifiers.functions.VotedPerceptron
  Set the value of exponent.
setExpression(String) - Method in class weka.filters.unsupervised.attribute.AddExpression
  Set the expression to apply
setFalseNegative(double) - Method in class weka.classifiers.evaluation.TwoClassStats
  Sets the number of positive instances predicted as negative
setFalsePositive(double) - Method in class weka.classifiers.evaluation.TwoClassStats
  Sets the number of negative instances predicted as positive
setFastRegression(boolean) - Method in class weka.classifiers.trees.LMT
  Set the value of fastRegression.
setFeatureSpaceNormalization(boolean) - Method in class weka.classifiers.functions.SMO
  Set whether feature space is normalized.
setFeatureSpaceNormalization(boolean) - Method in class weka.classifiers.functions.SMOreg
  Set whether feature space is normalized.
setFile(File) - Method in class weka.core.converters.AbstractFileSaver
  Sets the destination file.
setFile(File) - Method in class weka.core.converters.AbstractSaver
  Default implementation throws an IOException.
setFile(File) - Method in class weka.core.converters.ArffLoader
  sets the source File
setFile(File) - Method in class weka.core.converters.C45Loader
  sets the source File
setFile(File) - Method in class weka.core.converters.CSVLoader
  sets the source File
setFile(File) - Method in interface weka.core.converters.FileSourcedConverter
  Set the file to load from/ to save in
setFile(File) - Method in interface weka.core.converters.Saver
  Sets the output file
setFile(File) - Method in class weka.core.converters.SerializedInstancesLoader
  sets the source File
setFile(File) - Method in class weka.gui.visualize.JComponentWriter
  sets the file to store the output in
setFilename(String) - Method in class weka.gui.arffviewer.ArffPanel
  sets the filename
setFilename(int, String) - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  sets the filename of the specified panel
setFilePrefix(String) - Method in class weka.core.converters.AbstractFileSaver
  Sets the file name prefix
setFilePrefix(String) - Method in class weka.core.converters.AbstractSaver
  Default implementation throws an IOException.
setFilePrefix(String) - Method in interface weka.core.converters.Saver
  Sets the file prefix.
setFillWithMissing(boolean) - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries
  Sets whether missing values should be used rather than removing instances where the translated value is not known (due to border effects).
setFilter(Filter) - Method in class weka.classifiers.meta.FilteredClassifier
  Sets the filter
setFilter(Filter) - Method in class weka.gui.beans.Filter
  Set the filter to be wrapped by this bean
setFilterType(SelectedTag) - Method in class weka.attributeSelection.SVMAttributeEval
  The filtering mode to pass to SMO
setFilterType(SelectedTag) - Method in class weka.classifiers.functions.SMO
  Sets how the training data will be transformed.
setFilterType(SelectedTag) - Method in class weka.classifiers.functions.SMOreg
  Sets how the training data will be transformed.
setFindNumBins(boolean) - Method in class weka.filters.unsupervised.attribute.Discretize
  Set the value of FindNumBins.
setFindNumBins(boolean) - Method in class weka.filters.unsupervised.attribute.PKIDiscretize
  Set the value of FindNumBins.
setFirstValueIndex(String) - Method in class weka.filters.unsupervised.attribute.MergeTwoValues
  Sets index of the first value used.
setFirstValueIndex(String) - Method in class weka.filters.unsupervised.attribute.SwapValues
  Sets index of the first value used.
setFold(int) - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds
  Selects a fold.
setFold(int) - Method in class weka.filters.unsupervised.instance.RemoveFolds
  Selects a fold.
setFoldColumn(int) - Method in class weka.experiment.PairedTTester
  Set the value of FoldColumn.
setFolds(int) - Method in class weka.attributeSelection.AttributeSelection
  set the number of folds for cross validation
setFolds(int) - Method in class weka.attributeSelection.OneRAttributeEval
  Set the number of folds to use for cross validation
setFolds(int) - Method in class weka.attributeSelection.WrapperSubsetEval
  Set the number of folds to use for accuracy estimation
setFolds(int) - Method in class weka.classifiers.rules.ConjunctiveRule
setFolds(int) - Method in class weka.classifiers.rules.JRip
setFolds(int) - Method in class weka.classifiers.rules.Ridor
setFolds(int) - Method in class weka.gui.beans.CrossValidationFoldMaker
  Set the number of folds for the cross validation
setFoldsType(SelectedTag) - Method in class weka.attributeSelection.RaceSearch
  Set the xfold type
setFont(Font) - Method in class weka.gui.visualize.PostscriptGraphics
  Set current font.
setFrequencyThreshold(double) - Method in class weka.associations.Tertius
  Set the value of frequencyThreshold.
setFunctionValue(int, double) - Method in class weka.classifiers.functions.pace.DiscreteFunction
  Sets a particular function value
setGamma(double) - Method in class weka.classifiers.functions.SMO
  Set the value of gamma.
setGamma(double) - Method in class weka.classifiers.functions.SMOreg
  Set the value of gamma.
setGenerateRanking(boolean) - Method in class weka.attributeSelection.GreedyStepwise
  Records whether the user has requested a ranked list of attributes.
setGenerateRanking(boolean) - Method in class weka.attributeSelection.RaceSearch
  Records whether the user has requested a ranked list of attributes.
setGenerateRanking(boolean) - Method in interface weka.attributeSelection.RankedOutputSearch
  Sets whether or not ranking is to be performed.
setGenerateRanking(boolean) - Method in class weka.attributeSelection.Ranker
  This is a dummy set method---Ranker is ONLY capable of producing a ranked list of attributes for attribute evaluators.
setGeneratorSamplesBase(double) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel
  Set the base for computing the number of samples to obtain from each generator.
setGeneratorSamplesBase(double) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
  Set the base for computing the number of samples to obtain from each generator.
setGlobalBlend(int) - Method in class weka.classifiers.lazy.KStar
  Set the global blend parameter
setGlobalModel(NBTreeNoSplit) - Method in class weka.classifiers.trees.j48.NBTreeSplit
  Set the global naive bayes model for this node
setGridWidth(int) - Method in class weka.gui.beans.AttributeSummarizer
  Set the width of the grid of plots
setGUI(boolean) - Method in class weka.classifiers.functions.MultilayerPerceptron
  This will set whether A GUI is brought up to allow interaction by the user with the neural network during training.
setHandleRightClicks(boolean) - Method in class weka.gui.ResultHistoryPanel
  Set whether the result history list should handle right clicks or whether the parent object will handle them.
setHeuristicStop(int) - Method in class weka.classifiers.functions.SimpleLogistic
  Set the value of heuristicStop.
setHeuristicStop(int) - Method in class weka.classifiers.trees.lmt.LogisticBase
  Sets the option "heuristicStop".
setHidden(boolean) - Method in class weka.gui.beans.BeanConnection
  Make this connection invisible on the display
setHiddenLayers(String) - Method in class weka.classifiers.functions.MultilayerPerceptron
  This will set what the hidden layers are made up of when auto build is enabled.
setHighlight(String) - Method in class weka.gui.treevisualizer.TreeVisualizer
  Set the highlight for the node with the given id
setHoldOutFile(File) - Method in class weka.attributeSelection.ClassifierSubsetEval
  Set the file that contains hold out/test instances
setHornClauses(boolean) - Method in class weka.associations.Tertius
  Set the value of hornClauses.
setIDFTransform(boolean) - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Sets whether if the word frequencies in a document should be transformed into:
  fij*log(num of Docs/num of Docs with word i)
  where fij is the frequency of word i in document(instance) j.
setIgnoreClass(boolean) - Method in class weka.filters.unsupervised.attribute.PotentialClassIgnorer
  Set the IgnoreClass value.
setIgnoredAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.AddCluster
  Sets the ranges of attributes to be ignored.
setIgnoredAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.ClusterMembership
  Sets the ranges of attributes to be ignored.
setIncludeClass(boolean) - Method in class weka.core.InstanceComparator
  sets whether the class should be included (= TRUE) in the comparison
setInitAsNaiveBayes(boolean) - Method in class weka.classifiers.bayes.net.search.global.HillClimber
  Method declaration
setInitAsNaiveBayes(boolean) - Method in class weka.classifiers.bayes.net.search.global.K2
  Method declaration
setInitAsNaiveBayes(boolean) - Method in class weka.classifiers.bayes.net.search.local.HillClimber
  Method declaration
setInitAsNaiveBayes(boolean) - Method in class weka.classifiers.bayes.net.search.local.K2
  Method declaration
setInputFilename(String) - Method in class weka.gui.GenericPropertiesCreator
  sets the file to get the information about the packages from.
setInputFormat(Instances) - Method in class weka.filters.AllFilter
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.Filter
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.NullFilter
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.supervised.attribute.ClassOrder
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.supervised.attribute.Discretize
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.supervised.attribute.NominalToBinary
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.supervised.instance.Resample
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.supervised.instance.SpreadSubsample
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.Add
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.AddCluster
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.AddExpression
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.AddNoise
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat
  {@inheritDoc
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.ClusterMembership
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.Copy
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.Discretize
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.FirstOrder
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.MakeIndicator
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.MergeTwoValues
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.NominalToBinary
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.Normalize
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.NumericToBinary
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.NumericTransform
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.Obfuscate
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.PKIDiscretize
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.PotentialClassIgnorer
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.RandomProjection
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.Remove
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.RemoveType
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.RemoveUseless
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.ReplaceMissingValues
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.Standardize
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.StringToNominal
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.SwapValues
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.TimeSeriesDelta
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.TimeSeriesTranslate
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.NonSparseToSparse
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.Normalize
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.Randomize
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveFolds
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveMisclassified
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemovePercentage
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveRange
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveWithValues
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.Resample
  Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.SparseToNonSparse
  Sets the format of the input instances.
setInputOrder(int) - Method in class weka.datagenerators.BIRCHCluster
  Sets the input order.
setInputs(Vector) - Method in class weka.gui.beans.MetaBean
setInstance(Instance) - Method in class weka.gui.beans.InstanceEvent
  Set the instance
setInstanceIndex(int, boolean) - Method in class weka.classifiers.lazy.LBR.Indexes
  Changes the boolean value at the specified index in the InstIndexes array
setInstanceRange(int) - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries
  Sets the number of instances forward to translate values between.
setInstances(Instances) - Method in class weka.core.converters.AbstractSaver
  Sets instances that should be stored.
setInstances(Instances) - Method in interface weka.core.converters.Saver
  Sets the instances to be saved
setInstances(Instances) - Method in class weka.experiment.AveragingResultProducer
  Sets the dataset that results will be obtained for.
setInstances(Instances) - Method in class weka.experiment.CrossValidationResultProducer
  Sets the dataset that results will be obtained for.
setInstances(Instances) - Method in class weka.experiment.DatabaseResultProducer
  Sets the dataset that results will be obtained for.
setInstances(Instances) - Method in class weka.experiment.LearningRateResultProducer
  Sets the dataset that results will be obtained for.
setInstances(Instances) - Method in class weka.experiment.PairedTTester
  Set the value of Instances.
setInstances(Instances) - Method in class weka.experiment.RandomSplitResultProducer
  Sets the dataset that results will be obtained for.
setInstances(Instances) - Method in interface weka.experiment.ResultProducer
  Sets the dataset that results will be obtained for.
setInstances(Instances) - Method in class weka.gui.arffviewer.ArffPanel
  displays the given instances, i.e.
setInstances(Instances) - Method in class weka.gui.arffviewer.ArffTableModel
  sets the data
setInstances(Instances) - Method in class weka.gui.arffviewer.ArffTableSorter
  sets the data
setInstances(Instances) - Method in class weka.gui.AttributeListPanel
  Sets the instances who's attribute names will be displayed.
setInstances(Instances) - Method in class weka.gui.AttributeSelectionPanel
  Sets the instances who's attribute names will be displayed.
setInstances(Instances) - Method in class weka.gui.AttributeSummaryPanel
  Tells the panel to use a new set of instances.
setInstances(Instances) - Method in class weka.gui.AttributeVisualizationPanel
  Sets the instances for use
setInstances(Instances) - Method in class weka.gui.beans.AttributeSummarizer
  Set instances for this bean.
setInstances(Instances) - Method in class weka.gui.beans.DataVisualizer
  Set instances for this bean.
setInstances(Instances) - Method in class weka.gui.beans.ScatterPlotMatrix
  Set instances for this bean.
setInstances(Instances) - Method in class weka.gui.boundaryvisualizer.BoundaryVisualizer
  Set the training instances
setInstances(Instances) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
  Set the training data
setInstances(Instances) - Method in class weka.gui.experiment.ResultsPanel
  Sets up the panel with a new set of instances, attempting to guess the correct settings for various columns.
setInstances(Instances) - Method in class weka.gui.explorer.AssociationsPanel
  Tells the panel to use a new set of instances.
setInstances(Instances) - Method in class weka.gui.explorer.AttributeSelectionPanel
  Tells the panel to use a new set of instances.
setInstances(Instances) - Method in class weka.gui.explorer.ClassifierPanel
  Tells the panel to use a new set of instances.
setInstances(Instances) - Method in class weka.gui.explorer.ClustererPanel
  Tells the panel to use a new set of instances.
setInstances(Instances) - Method in class weka.gui.explorer.PreprocessPanel
  Tells the panel to use a new base set of instances.
setInstances(Instances) - Method in class weka.gui.InstancesSummaryPanel
  Tells the panel to use a new set of instances.
setInstances(Instances) - Method in class weka.gui.SetInstancesPanel
  Updates the set of instances that is currently held by the panel
setInstances(Instances) - Method in class weka.gui.ViewerDialog
  sets the instances to display
setInstances(Instances) - Method in class weka.gui.visualize.AttributePanel
  This sets the instances to be drawn into the attribute panel
setInstances(Instances) - Method in class weka.gui.visualize.ClassPanel
  Set the instances.
setInstances(Instances) - Method in class weka.gui.visualize.MatrixPanel
  This method changes the Instances object of this class to a new one.
setInstances(Instances) - Method in class weka.gui.visualize.Plot2D
  Sets the master plot from a set of instances
setInstances(Instances) - Method in class weka.gui.visualize.VisualizePanel
  Tells the panel to use a new set of instances.
setInstancesFromDB(InstanceQuery) - Method in class weka.gui.explorer.PreprocessPanel
  Loads instances from a database
setInstancesFromDBQ() - Method in class weka.gui.explorer.PreprocessPanel
  Queries the user for a URL to a database to load instances from, then loads the instances in a background process.
setInstancesFromFile(File) - Method in class weka.gui.explorer.PreprocessPanel
  Loads results from a set of instances contained in the supplied file.
setInstancesFromFileQ() - Method in class weka.gui.explorer.PreprocessPanel
  Queries the user for a file to load instances from, then loads the instances in a background process.
setInstancesFromFileQ() - Method in class weka.gui.SetInstancesPanel
  Queries the user for a file to load instances from, then loads the instances in a background process.
setInstancesFromURL(URL) - Method in class weka.gui.explorer.PreprocessPanel
  Loads instances from a URL.
setInstancesFromURLQ() - Method in class weka.gui.explorer.PreprocessPanel
  Queries the user for a URL to load instances from, then loads the instances in a background process.
setInstancesFromURLQ() - Method in class weka.gui.SetInstancesPanel
  Queries the user for a URL to load instances from, then loads the instances in a background process.
setInstancesIndices(String) - Method in class weka.filters.unsupervised.instance.RemoveRange
  Sets the ranges of instances to be selected.
SetInstancesPanel - Class in weka.gui
  A panel that displays an instance summary for a set of instances and lets the user open a set of instances from either a file or URL.
SetInstancesPanel() - Constructor for class weka.gui.SetInstancesPanel
  Create the panel.
setInstNums(String) - Method in class weka.datagenerators.BIRCHCluster
  Sets the upper and lower boundary for instances per cluster.
setInsts(int[], boolean) - Method in class weka.classifiers.lazy.LBR.Indexes
  Changes the boolean value at the specified index in the InstIndexes array
setInvert(boolean) - Method in class weka.core.Range
  Sets whether the range sense is inverted, i.e.
setInvert(boolean) - Method in class weka.filters.unsupervised.instance.RemoveMisclassified
  Set whether selection is inverted.
setInvertSelection(boolean) - Method in class weka.filters.supervised.attribute.Discretize
  Sets whether selected columns should be removed or kept.
setInvertSelection(boolean) - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds
  Sets if selection is to be inverted.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries
  Set whether selected columns should be removed or kept.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.Copy
  Set whether selected columns should be removed or kept.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.Discretize
  Sets whether selected columns should be removed or kept.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.NominalToBinary
  Sets whether selected columns should be removed or kept.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.NumericTransform
  Set whether selected columns should be transformed or not.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.Remove
  Set whether selected columns should be removed or kept.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.RemoveType
  Set whether selected columns should be removed or kept.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.instance.RemoveFolds
  Sets if selection is to be inverted.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.instance.RemovePercentage
  Sets if selection is to be inverted.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.instance.RemoveRange
  Sets if selection is to be inverted.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.instance.RemoveWithValues
  Set whether selected values should be removed or kept.
setItem(int[]) - Method in class weka.associations.ItemSet
  Sets an item sets
setItemAt(int, int) - Method in class weka.associations.ItemSet
  Sets the index of an attribute value
setJitter(int) - Method in class weka.gui.visualize.Plot2D
  Set level of jitter and repaint the plot using the new jitter value
setKernelBandwidth(int) - Method in class weka.gui.boundaryvisualizer.KDDataGenerator
  Set the kernel bandwidth (number of nearest neighbours to cover)
setKeyFieldName(String) - Method in class weka.experiment.AveragingResultProducer
  Set the value of KeyFieldName.
setKeys(String) - Method in class weka.core.converters.DatabaseLoader
  Sets the key columns of a database table
setKNN(int) - Method in class weka.classifiers.lazy.IBk
  Set the number of neighbours the learner is to use.
setKNN(int) - Method in class weka.classifiers.lazy.LWL
  Sets the number of neighbours used for kernel bandwidth setting.
setKValue(int) - Method in class weka.classifiers.trees.RandomTree
  Set the value of K.
setLearningRate(double) - Method in class weka.classifiers.functions.MultilayerPerceptron
  The learning rate can be set using this command.
setLegendText(Vector) - Method in class weka.gui.beans.ChartEvent
  Set the legend text vector
setLikelihoodThreshold(double) - Method in class weka.classifiers.meta.LogitBoost
  Set the value of Precision.
setLNorm(double) - Method in class weka.filters.unsupervised.instance.Normalize
  Set the L-norm to used
setLoader(Loader) - Method in class weka.gui.beans.Loader
  Set the loader to use
setLocallyPredictive(boolean) - Method in class weka.attributeSelection.CfsSubsetEval
  Include locally predictive attributes
setLocationProbs(int, double[]) - Method in class weka.gui.boundaryvisualizer.RemoteResult
  Store the classifier's distribution for a particular pixel in the visualization
setLog(Logger) - Method in class weka.gui.beans.AbstractDataSink
  Set a log for this bean
setLog(Logger) - Method in class weka.gui.beans.AbstractEvaluator
  Set a logger
setLog(Logger) - Method in class weka.gui.beans.AbstractTestSetProducer
  Set a logger
setLog(Logger) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer
  Set a log for this bean
setLog(Logger) - Method in class weka.gui.beans.AbstractTrainingSetProducer
  Set a logger
setLog(Logger) - Method in interface weka.gui.beans.BeanCommon
  Set a logger
setLog(Logger) - Method in class weka.gui.beans.ClassAssigner
setLog(Logger) - Method in class weka.gui.beans.Classifier
  Set a logger
setLog(Logger) - Method in class weka.gui.beans.ClassValuePicker
setLog(Logger) - Method in class weka.gui.beans.Clusterer
  Set a logger
setLog(Logger) - Method in class weka.gui.beans.Filter
  Set a logger
setLog(Logger) - Method in class weka.gui.beans.MetaBean
  Set a logger
setLog(Logger) - Method in class weka.gui.beans.PredictionAppender
  Set a logger
setLog(Logger) - Method in class weka.gui.beans.StripChart
  Set a logger
setLog(Logger) - Method in class weka.gui.explorer.AssociationsPanel
  Sets the Logger to receive informational messages
setLog(Logger) - Method in class weka.gui.explorer.AttributeSelectionPanel
  Sets the Logger to receive informational messages
setLog(Logger) - Method in class weka.gui.explorer.ClassifierPanel
  Sets the Logger to receive informational messages
setLog(Logger) - Method in class weka.gui.explorer.ClustererPanel
  Sets the Logger to receive informational messages
setLog(Logger) - Method in class weka.gui.explorer.PreprocessPanel
  Sets the Logger to receive informational messages
setLog(Logger) - Method in class weka.gui.visualize.VisualizePanel
  Sets the Logger to receive informational messages
setLookAndFeel(String) - Static method in class weka.gui.LookAndFeel
  sets the look and feel to the specified class
setLookAndFeel() - Static method in class weka.gui.LookAndFeel
  sets the look and feel to the one in the props-file or if not set the default one of the system
setLookupCacheSize(int) - Method in class weka.attributeSelection.BestFirst
  Set the maximum size of the evaluated subset cache (hashtable).
setLowerBoundMinSupport(double) - Method in class weka.associations.Apriori
  Set the value of lowerBoundMinSupport.
setLowerCaseTokens(boolean) - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Sets whether if the tokens are to be downcased or not.
setLowerOrderTerms(boolean) - Method in class weka.classifiers.functions.SMO
  Set whether lower-order terms are to be used.
setLowerOrderTerms(boolean) - Method in class weka.classifiers.functions.SMOreg
  Set whether lower-order terms are to be used.
setLowerSize(int) - Method in class weka.experiment.LearningRateResultProducer
  Set the value of LowerSize.
setMajorityClass(boolean) - Method in class weka.classifiers.rules.Ridor
setMakeBinary(boolean) - Method in class weka.filters.supervised.attribute.Discretize
  Sets whether binary attributes should be made for discretized ones.
setMakeBinary(boolean) - Method in class weka.filters.unsupervised.attribute.Discretize
  Sets whether binary attributes should be made for discretized ones.
setMarkovBlanketClassifier(boolean) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
setMarkovBlanketClassifier(boolean) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
setMasterPlot(PlotData2D) - Method in class weka.gui.visualize.Plot2D
  Set the master plot.
setMasterPlot(PlotData2D) - Method in class weka.gui.visualize.VisualizePanel
  Set the master plot for the visualize panel
setMatchMissingValues(boolean) - Method in class weka.filters.unsupervised.instance.RemoveWithValues
  Sets whether missing values are counted as a match.
setMatrix(int, int, int, int, Matrix) - Method in class weka.classifiers.functions.pace.Matrix
  Set a submatrix.
setMatrix(int[], int[], Matrix) - Method in class weka.classifiers.functions.pace.Matrix
  Set a submatrix.
setMatrix(int[], int, int, Matrix) - Method in class weka.classifiers.functions.pace.Matrix
  Set a submatrix.
setMatrix(int, int, int[], Matrix) - Method in class weka.classifiers.functions.pace.Matrix
  Set a submatrix.
setMatrix(int, int, int, int, double) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Set the submatrix A[i0:i1][j0:j1] with a same value
setMatrix(int, int, int, DoubleVector) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Set the submatrix A[i0:i1][j] with the values stored in a DoubleVector
setMatrix(double[], boolean) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Set the whole matrix from a 1-D array
setMatrix(int, int, int, int, Matrix) - Method in class weka.core.matrix.Matrix
  Set a submatrix.
setMatrix(int[], int[], Matrix) - Method in class weka.core.matrix.Matrix
  Set a submatrix.
setMatrix(int[], int, int, Matrix) - Method in class weka.core.matrix.Matrix
  Set a submatrix.
setMatrix(int, int, int[], Matrix) - Method in class weka.core.matrix.Matrix
  Set a submatrix.
setMax(double) - Method in class weka.gui.beans.ChartEvent
  Set the max y value
setMaxBoostingIterations(int) - Method in class weka.classifiers.functions.SimpleLogistic
  Set the value of maxBoostingIterations.
setMaxCardinality(int) - Method in class weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm
setMaxChunkSize(int) - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost
  Set the maximum chunk size
setMaxCount(double) - Method in class weka.filters.supervised.instance.SpreadSubsample
  Sets the value for the max count
setMaxDepth(int) - Method in class weka.classifiers.trees.REPTree
  Set the value of MaxDepth.
setMaxGenerations(int) - Method in class weka.attributeSelection.GeneticSearch
  set the number of generations to evaluate
setMaximumAttributeNames(int) - Method in class weka.attributeSelection.PrincipalComponents
  Sets maximum number of attributes to include in transformed attribute names.
setMaximumVariancePercentageAllowed(double) - Method in class weka.filters.unsupervised.attribute.RemoveUseless
  Sets the maximum variance attributes are allowed to have before they are deleted by the filter.
setMaxInstNum(int) - Method in class weka.datagenerators.BIRCHCluster
  Sets the upper boundary for instances per cluster.
setMaxIteration(int) - Method in class weka.core.Optimization
  Set the maximal number of iterations in searching (Default 200)
setMaxIterations(int) - Method in class weka.classifiers.trees.lmt.LogisticBase
  Sets the parameter "maxIterations".
setMaxIterations(int) - Method in class weka.clusterers.EM
  Set the maximum number of iterations to perform
setMaxIterations(int) - Method in class weka.filters.unsupervised.instance.RemoveMisclassified
  Sets the maximum number of cleansing iterations to perform - < 1 means go until fully cleansed
setMaxIts(int) - Method in class weka.classifiers.functions.Logistic
  Set the value of MaxIts.
setMaxIts(int) - Method in class weka.classifiers.functions.RBFNetwork
  Set the value of MaxIts.
setMaxK(int) - Method in class weka.classifiers.functions.VotedPerceptron
  Set the value of maxK.
setMaxNrOfParents(int) - Method in class weka.classifiers.bayes.net.search.global.HillClimber
  Method declaration
setMaxNrOfParents(int) - Method in class weka.classifiers.bayes.net.search.global.K2
  Method declaration
setMaxNrOfParents(int) - Method in class weka.classifiers.bayes.net.search.local.HillClimber
  Method declaration
setMaxNrOfParents(int) - Method in class weka.classifiers.bayes.net.search.local.K2
  Method declaration
setMaxPlots(int) - Method in class weka.gui.beans.AttributeSummarizer
  Set the maximum number of plots to display
setMaxRadius(double) - Method in class weka.datagenerators.BIRCHCluster
  Sets the upper boundary for the radiuses of the clusters.
setMaxRuleSize(int) - Method in class weka.datagenerators.RDG1
  Sets the maximum number of tests in rules.
setMaxStale(int) - Method in class weka.classifiers.rules.DecisionTable
  Sets the number of non improving decision tables to consider before abandoning the search.
setMDLTheoryWeight(double) - Method in class weka.classifiers.rules.RuleStats
  Set the weight of theory in MDL calcualtion
setMeanPrec(int) - Method in class weka.experiment.PairedTTester
  Sets the precision of the mean output
setMeanPrec(int) - Method in class weka.gui.experiment.OutputFormatDialog
  Sets the precision of the mean output
setMeanSquared(boolean) - Method in class weka.classifiers.lazy.IBk
  Sets whether the mean squared error is used rather than mean absolute error when doing cross-validation.
setMetaClassifier(Classifier) - Method in class weka.classifiers.meta.Stacking
  Adds meta classifier
setMethod(NeuralMethod) - Method in class weka.classifiers.functions.neural.NeuralNode
  Set how this node should operate (note that the neural method has no internal state, so the same object can be used by any number of nodes.
setMethod(SelectedTag) - Method in class weka.classifiers.meta.MultiClassClassifier
  Sets the method used.
setMethodName(String) - Method in class weka.filters.unsupervised.attribute.NumericTransform
  Set the transformation method.
setMetricType(SelectedTag) - Method in class weka.associations.Apriori
  Set the metric type for ranking rules
setMin(double) - Method in class weka.gui.beans.ChartEvent
  Set the min y value
setMinBucketSize(int) - Method in class weka.classifiers.rules.OneR
  Set the value of minBucketSize.
setMinChunkSize(int) - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost
  Set the minimum chunk size
setMinimizeExpectedCost(boolean) - Method in class weka.classifiers.meta.CostSensitiveClassifier
  Set the value of MinimizeExpectedCost.
setMinimumBucketSize(int) - Method in class weka.attributeSelection.OneRAttributeEval
  Set the minumum bucket size used by OneR
setMinInstNum(int) - Method in class weka.datagenerators.BIRCHCluster
  Sets the lower boundary for instances per cluster.
setMinMaxX(double, double) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
  Set the minimum and maximum values of the x axis fixed dimension
setMinMaxY(double, double) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
  Set the minimum and maximum values of the y axis fixed dimension
setMinMetric(double) - Method in class weka.associations.Apriori
  Set the value of minConfidence.
setMinNo(double) - Method in class weka.classifiers.rules.ConjunctiveRule
setMinNo(double) - Method in class weka.classifiers.rules.JRip
setMinNo(double) - Method in class weka.classifiers.rules.Ridor
setMinNum(double) - Method in class weka.classifiers.trees.RandomTree
  Set the value of MinNum.
setMinNum(double) - Method in class weka.classifiers.trees.REPTree
  Set the value of MinNum.
setMinNumInstances(int) - Method in class weka.classifiers.trees.LMT
  Set the value of minNumInstances.
setMinNumInstances(double) - Method in class weka.classifiers.trees.m5.M5Base
  Set the minumum number of instances to allow at a leaf node
setMinNumInstances(double) - Method in class weka.classifiers.trees.m5.Rule
  Set the minumum number of instances to allow at a leaf node
setMinNumInstances(double) - Method in class weka.classifiers.trees.m5.RuleNode
  Set the minumum number of instances to allow at a leaf node
setMinNumObj(int) - Method in class weka.classifiers.rules.PART
  Set the value of minNumObj.
setMinNumObj(int) - Method in class weka.classifiers.trees.J48
  Set the value of minNumObj.
setMinRadius(double) - Method in class weka.datagenerators.BIRCHCluster
  Sets the lower boundary for the radiuses of the clusters.
setMinRuleSize(int) - Method in class weka.datagenerators.RDG1
  Sets the minimum number of tests in rules.
setMinStdDev(double) - Method in class weka.classifiers.functions.RBFNetwork
  Set the MinStdDev value.
setMinStdDev(double) - Method in class weka.clusterers.EM
  Set the minimum value for standard deviation when calculating normal density.
setMinStdDev(double) - Method in class weka.clusterers.MakeDensityBasedClusterer
  Set the minimum value for standard deviation when calculating normal density.
setMinStdDevPerAtt(double[]) - Method in class weka.clusterers.EM
setMinVarianceProp(double) - Method in class weka.classifiers.trees.REPTree
  Set the value of MinVarianceProp.
setMissing(int) - Method in class weka.core.Instance
  Sets a specific value to be "missing".
setMissing(Attribute) - Method in class weka.core.Instance
  Sets a specific value to be "missing".
setMissingMerge(boolean) - Method in class weka.attributeSelection.ChiSquaredAttributeEval
  distribute the counts for missing values across observed values
setMissingMerge(boolean) - Method in class weka.attributeSelection.GainRatioAttributeEval
  distribute the counts for missing values across observed values
setMissingMerge(boolean) - Method in class weka.attributeSelection.InfoGainAttributeEval
  distribute the counts for missing values across observed values
setMissingMerge(boolean) - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval
  distribute the counts for missing values across observed values
setMissingMode(int) - Method in class weka.classifiers.lazy.kstar.KStarNumericAttribute
  Set the missing value mode.
setMissingMode(SelectedTag) - Method in class weka.classifiers.lazy.KStar
  Sets the method to use for handling missing values.
setMissingSeperate(boolean) - Method in class weka.attributeSelection.CfsSubsetEval
  Treat missing as a seperate value
setMissingValues(SelectedTag) - Method in class weka.associations.Tertius
  Set the value of missingValues.
setMixingDistribution(DiscreteFunction) - Method in class weka.classifiers.functions.pace.MixtureDistribution
  Sets the mixing distribution
setModel(TableModel) - Method in class weka.gui.arffviewer.ArffTable
  sets the new model
setModel(TableModel) - Method in class weka.gui.TableMap
setModel(TableModel) - Method in class weka.gui.TableSorter
setModePanel(SetupModePanel) - Method in class weka.gui.experiment.SimpleSetupPanel
  Sets the panel used to switch between simple and advanced modes.
setModifyHeader(boolean) - Method in class weka.filters.unsupervised.instance.RemoveWithValues
  Sets whether the header will be modified when selecting on nominal attributes.
setMomentum(double) - Method in class weka.classifiers.functions.MultilayerPerceptron
  The momentum can be set using this command.
setMutationProb(double) - Method in class weka.attributeSelection.GeneticSearch
  set the probability of mutation
setName(String) - Method in class weka.filters.unsupervised.attribute.AddExpression
  Set the name for the new attribute.
setName(String) - Method in class weka.gui.visualize.VisualizePanel
  Set a name for this plot
setNegation(Literal) - Method in class weka.associations.tertius.Literal
setNegation(SelectedTag) - Method in class weka.associations.Tertius
  Set the value of negation.
setNodesEdges(FastVector, FastVector) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine
  Sets the nodes and edges for this LayoutEngine.
setNodesEdges(FastVector, FastVector) - Method in interface weka.gui.graphvisualizer.LayoutEngine
  This method sets the nodes and edges vectors of the LayoutEngine
setNodeSize(int, int) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine
  Sets the size of a node.
setNodeSize(int, int) - Method in interface weka.gui.graphvisualizer.LayoutEngine
  This method sets the allowed size of the node
setNoiseRate(double) - Method in class weka.datagenerators.BIRCHCluster
  Sets the percentage of noise set.
setNoiseThreshold(double) - Method in class weka.associations.Tertius
  Set the value of noiseThreshold.
setNominalIndices(String) - Method in class weka.filters.unsupervised.instance.RemoveWithValues
  Set which nominal labels are to be included in the selection.
setNominalIndicesArr(int[]) - Method in class weka.filters.unsupervised.instance.RemoveWithValues
  Set which values of a nominal attribute are to be used for selection.
setNominalLabels(String) - Method in class weka.filters.unsupervised.attribute.Add
  Set the labels for nominal attribute creation.
setNominalToBinaryFilter(boolean) - Method in class weka.classifiers.functions.MultilayerPerceptron
setNoNormalization(boolean) - Method in class weka.classifiers.lazy.IBk
  Set whether normalization is turned off.
setNoPruning(boolean) - Method in class weka.classifiers.trees.REPTree
  Set the value of NoPruning.
setNorm(double) - Method in class weka.filters.unsupervised.instance.Normalize
  Set the norm of the instances
setNormalize(boolean) - Method in class weka.attributeSelection.PrincipalComponents
  Set whether input data will be normalized.
setNormalizeAttributes(boolean) - Method in class weka.classifiers.functions.MultilayerPerceptron
setNormalizeDocLength(boolean) - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Sets whether if the word frequencies for a document (instance) should be normalized or not.
setNormalizeNumericClass(boolean) - Method in class weka.classifiers.functions.MultilayerPerceptron
setNormalizeWordWeights(boolean) - Method in class weka.classifiers.bayes.ComplementNaiveBayes
  Sets whether if the word weights for each class should be normalized
setNotes(String) - Method in class weka.experiment.Experiment
  Set the user notes.
setNotes(String) - Method in class weka.experiment.RemoteExperiment
  Set the user notes.
setNotificationEnabled(boolean) - Method in class weka.gui.arffviewer.ArffTableModel
  sets whether the notification of changes is enabled
setNotificationEnabled(boolean) - Method in class weka.gui.arffviewer.ArffTableSorter
  sets whether the notification of changes is enabled
setNumAllConds(double) - Method in class weka.classifiers.rules.RuleStats
  Set the number of all conditions that could appear in a rule in this RuleStats object, if the number set is smaller than 0 (typically -1), then it calcualtes based on the data store
setNumAntds(int) - Method in class weka.classifiers.rules.ConjunctiveRule
setNumAttemptsOfGeneOption(int) - Method in class weka.classifiers.rules.NNge
  Sets the number of attempts for generalisation.
setNumAttributes(int) - Method in class weka.datagenerators.ClusterGenerator
  Sets the number of attributes the dataset should have.
setNumAttributes(int) - Method in class weka.datagenerators.Generator
  Sets the number of attributes the dataset should have.
setNumberLiterals(int) - Method in class weka.associations.Tertius
  Set the value of numberLiterals.
setNumberOfAttributes(int) - Method in class weka.filters.unsupervised.attribute.RandomProjection
  Sets the number of attributes (dimensions) the data should be reduced to
setNumBins(int) - Method in class weka.classifiers.meta.RegressionByDiscretization
  Sets the number of bins to divide each selected numeric attribute into
setNumBoostingIterations(int) - Method in class weka.classifiers.functions.SimpleLogistic
  Set the value of numBoostingIterations.
setNumBoostingIterations(int) - Method in class weka.classifiers.trees.LMT
  Set the value of numBoostingIterations.
setNumClasses(int) - Method in class weka.datagenerators.Generator
  Sets the number of classes the dataset should have.
setNumClusters(int) - Method in class weka.classifiers.functions.RBFNetwork
  Set the number of clusters for K-means to generate.
setNumClusters(int) - Method in class weka.clusterers.EM
  Set the number of clusters (-1 to select by CV).
setNumClusters(int) - Method in class weka.clusterers.FarthestFirst
  set the number of clusters to generate
setNumClusters(int) - Method in class weka.clusterers.MakeDensityBasedClusterer
  Set the number of clusters to generate.
setNumClusters(int) - Method in interface weka.clusterers.NumberOfClustersRequestable
  Set the number of clusters to generate
setNumClusters(int) - Method in class weka.clusterers.SimpleKMeans
  set the number of clusters to generate
setNumClusters(int) - Method in class weka.datagenerators.ClusterGenerator
  Sets the number of clusters the dataset should have.
setNumCycles(int) - Method in class weka.datagenerators.BIRCHCluster
  Sets the the number of cycles.
setNumeric(boolean) - Method in class weka.filters.unsupervised.attribute.MakeIndicator
  Sets if the new Attribute is to be numeric.
setNumExamples(int) - Method in class weka.datagenerators.Generator
  Sets the number of examples, given by option.
setNumExamplesAct(int) - Method in class weka.datagenerators.ClusterGenerator
  Sets the number of examples the dataset should have.
setNumExamplesAct(int) - Method in class weka.datagenerators.Generator
  Sets the number of examples the dataset should have.
setNumFeatures(int) - Method in class weka.classifiers.trees.RandomForest
  Set the number of features to use in random selection.
setNumFoldersMIOption(int) - Method in class weka.classifiers.rules.NNge
  Sets the number of folder for mutual information.
setNumFolds(int) - Method in class weka.classifiers.functions.SMO
  Set the value of numFolds.
setNumFolds(int) - Method in class weka.classifiers.meta.CVParameterSelection
  Sets the number of folds for the cross-validation.
setNumFolds(int) - Method in class weka.classifiers.meta.LogitBoost
  Set the value of NumFolds.
setNumFolds(int) - Method in class weka.classifiers.meta.MultiScheme
  Sets the number of folds for cross-validation.
setNumFolds(int) - Method in class weka.classifiers.meta.Stacking
  Sets the number of folds for the cross-validation.
setNumFolds(int) - Method in class weka.classifiers.rules.PART
  Set the value of numFolds.
setNumFolds(int) - Method in class weka.classifiers.trees.J48
  Set the value of numFolds.
setNumFolds(int) - Method in class weka.classifiers.trees.REPTree
  Set the value of NumFolds.
setNumFolds(int) - Method in class weka.experiment.CrossValidationResultProducer
  Set the value of NumFolds.
setNumFolds(int) - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds
  Sets the number of folds the dataset is split into.
setNumFolds(int) - Method in class weka.filters.unsupervised.instance.RemoveFolds
  Sets the number of folds the dataset is split into.
setNumFolds(int) - Method in class weka.filters.unsupervised.instance.RemoveMisclassified
  Sets the number of cross-validation folds to use - < 2 means no cross-validation.
setNumInstances(int) - Method in class weka.classifiers.CheckClassifier
  Sets the number of instances to use in the datasets (some classifiers might require more instances).
setNumIrrelevant(int) - Method in class weka.datagenerators.RDG1
  Sets the number of irrelevant attributes.
setNumIterations(int) - Method in class weka.classifiers.functions.VotedPerceptron
  Set the value of NumIterations.
setNumIterations(int) - Method in class weka.classifiers.functions.Winnow
  Set the value of numIterations.
setNumIterations(int) - Method in class weka.classifiers.IteratedSingleClassifierEnhancer
  Sets the number of bagging iterations
setNumIterations(int) - Method in class weka.classifiers.meta.MetaCost
  Sets the number of bagging iterations
setNumNeighbours(int) - Method in class weka.attributeSelection.ReliefFAttributeEval
  Set the number of nearest neighbours
setNumNumeric(int) - Method in class weka.datagenerators.RDG1
  Sets the number of numerical attributes.
setNumOfBoostingIterations(int) - Method in class weka.classifiers.trees.ADTree
  Sets the number of boosting iterations.
setNumRules(int) - Method in class weka.associations.Apriori
  Set the value of numRules.
setNumRules(int) - Method in class weka.associations.PredictiveApriori
  Set the value of required rules.
setNumRuns(int) - Method in class weka.classifiers.meta.LogitBoost
  Set the value of NumRuns.
setNumSamplesPerRegion(int) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel
  Set the number of points to uniformly sample from a region (fixed dimensions).
setNumSamplesPerRegion(int) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
  Set the number of points to uniformly sample from a region (fixed dimensions).
setNumSubCmtys(int) - Method in class weka.classifiers.meta.MultiBoostAB
  Set the number of sub committees to use
setNumToSelect(int) - Method in class weka.attributeSelection.GreedyStepwise
  Specify the number of attributes to select from the ranked list (if generating a ranking).
setNumToSelect(int) - Method in class weka.attributeSelection.RaceSearch
  Specify the number of attributes to select from the ranked list (if generating a ranking).
setNumToSelect(int) - Method in interface weka.attributeSelection.RankedOutputSearch
  Specify the number of attributes to select from the ranked list.
setNumToSelect(int) - Method in class weka.attributeSelection.Ranker
  Specify the number of attributes to select from the ranked list.
setNumTrees(int) - Method in class weka.classifiers.trees.RandomForest
  Set the value of numTrees.
setNumXValFolds(int) - Method in class weka.classifiers.meta.ThresholdSelector
  Set the number of folds used for cross-validation.
setObject(Object) - Method in class weka.gui.beans.ClassAssignerCustomizer
  Set the bean to be edited
setObject(Object) - Method in class weka.gui.beans.ClassifierCustomizer
  Set the classifier object to be edited
setObject(Object) - Method in class weka.gui.beans.ClassValuePickerCustomizer
  Set the bean to be edited
setObject(Object) - Method in class weka.gui.beans.ClustererCustomizer
  Set the Clusterer object to be edited
setObject(Object) - Method in class weka.gui.beans.CrossValidationFoldMakerCustomizer
  Set the object to be edited
setObject(Object) - Method in class weka.gui.beans.FilterCustomizer
  Set the filter bean to be edited
setObject(Object) - Method in class weka.gui.beans.LoaderCustomizer
  Set the loader to be customized
setObject(Object) - Method in class weka.gui.beans.PredictionAppenderCustomizer
  Set the object to be edited
setObject(Object) - Method in class weka.gui.beans.SaverCustomizer
  Set the saver to be customized
setObject(Object) - Method in class weka.gui.beans.StripChartCustomizer
  Set the StripChart object to be customized
setObject(Object) - Method in class weka.gui.beans.TrainTestSplitMakerCustomizer
  Set the TrainTestSplitMaker to be customized
setOkButtonText(String) - Method in class weka.gui.GenericObjectEditor.GOEPanel
  Allows customization of the action label on the dialog.
setOn(boolean) - Method in class weka.gui.visualize.ClassPanel
  Enables the panel
setOnDemandDirectory(File) - Method in class weka.classifiers.meta.CostSensitiveClassifier
  Sets the directory that will be searched for cost files when loading on demand.
setOnDemandDirectory(File) - Method in class weka.classifiers.meta.MetaCost
  Sets the directory that will be searched for cost files when loading on demand.
setOnDemandDirectory(File) - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator
  Sets the directory that will be searched for cost files when loading on demand.
setOnlyAlphabeticTokens(boolean) - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Sets whether if tokens are to be formed only from contiguous alphabetic character sequences.
setOptimalColumnWidth(int) - Method in class weka.gui.JTableHelper
  sets the optimal column width for the given column
setOptimalColumnWidth(JTable, int) - Static method in class weka.gui.JTableHelper
  sets the optimal column width for the given column
setOptimalColumnWidth() - Method in class weka.gui.JTableHelper
  sets the optimal column width for all columns
setOptimalColumnWidth(JTable) - Static method in class weka.gui.JTableHelper
  sets the optimal column width for alls column if the given table
setOptimalHeaderWidth(int) - Method in class weka.gui.JTableHelper
  sets the optimal header width for the given column
setOptimalHeaderWidth(JTable, int) - Static method in class weka.gui.JTableHelper
  sets the optimal header width for the given column
setOptimalHeaderWidth() - Method in class weka.gui.JTableHelper
  sets the optimal header width for all columns
setOptimalHeaderWidth(JTable) - Static method in class weka.gui.JTableHelper
  sets the optimal header width for alls column if the given table
setOptimizations(int) - Method in class weka.classifiers.rules.JRip
setOptions(String[]) - Method in class weka.associations.Apriori
  Parses a given list of options.
setOptions(String[]) - Method in class weka.associations.PredictiveApriori
  Parses a given list of options.
setOptions(String[]) - Method in class weka.associations.Tertius
  Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.BestFirst
  Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.CfsSubsetEval
  Parses and sets a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.ChiSquaredAttributeEval
  Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.ClassifierSubsetEval
  Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.ExhaustiveSearch
  Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.GainRatioAttributeEval
  Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.GeneticSearch
  Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.GreedyStepwise
  Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.InfoGainAttributeEval
  Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.OneRAttributeEval
  Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.PrincipalComponents
  Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.RaceSearch
  Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.RandomSearch
  Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.Ranker
  Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.RankSearch
  Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.ReliefFAttributeEval
  Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.SVMAttributeEval
  Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval
  Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.WrapperSubsetEval
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.AODE
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.BayesNet
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.ComplementNaiveBayes
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.NaiveBayes
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.BayesNetGenerator
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.estimate.BMAEstimator
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.fixed.FromFile
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.global.HillClimber
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.global.K2
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.global.TabuSearch
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.global.TAN
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.local.HillClimber
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.local.K2
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.local.TabuSearch
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.local.TAN
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.SearchAlgorithm
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.BVDecompose
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.BVDecomposeSegCVSub
  Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.classifiers.CheckClassifier
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.Classifier
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.LeastMedSq
  Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.classifiers.functions.LinearRegression
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.Logistic
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.MultilayerPerceptron
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.PaceRegression
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.RBFNetwork
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.SimpleLogistic
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.SMO
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.SMOreg
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.VotedPerceptron
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.Winnow
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.IteratedSingleClassifierEnhancer
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.lazy.IBk
  Parses a given list of options.
setOptions(int, int, int) - Method in class weka.classifiers.lazy.kstar.KStarNominalAttribute
  Sets the options.
setOptions(int, int, int) - Method in class weka.classifiers.lazy.kstar.KStarNumericAttribute
  Set options.
setOptions(String[]) - Method in class weka.classifiers.lazy.KStar
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.lazy.LWL
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.AdaBoostM1
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.AdditiveRegression
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.AttributeSelectedClassifier
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.Bagging
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.CostSensitiveClassifier
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.CVParameterSelection
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.Decorate
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.FilteredClassifier
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.LogitBoost
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.MetaCost
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.MultiBoostAB
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.MultiClassClassifier
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.MultiScheme
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.OrdinalClassClassifier
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.RegressionByDiscretization
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.Stacking
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.ThresholdSelector
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.misc.VFI
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.MultipleClassifiersCombiner
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.RandomizableClassifier
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.RandomizableIteratedSingleClassifierEnhancer
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.RandomizableMultipleClassifiersCombiner
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.RandomizableSingleClassifierEnhancer
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.rules.ConjunctiveRule
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.rules.DecisionTable
  Parses the options for this object.
setOptions(String[]) - Method in class weka.classifiers.rules.JRip
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.rules.NNge
  Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.classifiers.rules.OneR
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.rules.PART
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.rules.Ridor
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.SingleClassifierEnhancer
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.trees.ADTree
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.trees.J48
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.trees.LMT
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.trees.m5.M5Base
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.trees.M5P
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.trees.RandomForest
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.trees.RandomTree
  Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.trees.REPTree
  Parses a given list of options.
setOptions(String[]) - Method in class weka.clusterers.Cobweb
  Parses a given list of options.
setOptions(String[]) - Method in class weka.clusterers.EM
  Parses a given list of options.
setOptions(String[]) - Method in class weka.clusterers.FarthestFirst
  Parses a given list of options.
setOptions(String[]) - Method in class weka.clusterers.MakeDensityBasedClusterer
  Parses a given list of options.
setOptions(String[]) - Method in class weka.clusterers.SimpleKMeans
  Parses a given list of options.
setOptions(String[]) - Method in class weka.core.converters.AbstractFileSaver
  Parses a given list of options.
setOptions(String[]) - Method in class weka.core.converters.C45Saver
  Parses a given list of options.
setOptions(String[]) - Method in class weka.core.converters.DatabaseLoader
  Sets the options.
setOptions(String[]) - Method in class weka.core.converters.DatabaseSaver
  Sets the options.
setOptions(String[]) - Method in interface weka.core.OptionHandler
  Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.datagenerators.BIRCHCluster
  Parses a list of options for this object.
setOptions(String[]) - Method in class weka.datagenerators.RDG1
  Parses a list of options for this object.
setOptions(String[]) - Method in class weka.experiment.AveragingResultProducer
  Parses a given list of options.
setOptions(String[]) - Method in class weka.experiment.ClassifierSplitEvaluator
  Parses a given list of options.
setOptions(String[]) - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator
  Parses a given list of options.
setOptions(String[]) - Method in class weka.experiment.CrossValidationResultProducer
  Parses a given list of options.
setOptions(String[]) - Method in class weka.experiment.CSVResultListener
  Parses a given list of options.
setOptions(String[]) - Method in class weka.experiment.DatabaseResultProducer
  Parses a given list of options.
setOptions(String[]) - Method in class weka.experiment.Experiment
  Parses a given list of options.
setOptions(String[]) - Method in class weka.experiment.InstanceQuery
  Parses a given list of options.
setOptions(String[]) - Method in class weka.experiment.LearningRateResultProducer
  Parses a given list of options.
setOptions(String[]) - Method in class weka.experiment.PairedTTester
  Parses a given list of options.
setOptions(String[]) - Method in class weka.experiment.RandomSplitResultProducer
  Parses a given list of options.
setOptions(String[]) - Method in class weka.experiment.RegressionSplitEvaluator
  Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.supervised.attribute.AttributeSelection
  Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.supervised.attribute.ClassOrder
  Parses a given list of options controlling the behaviour of this object.
setOptions(String[]) - Method in class weka.filters.supervised.attribute.Discretize
  Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.supervised.attribute.NominalToBinary
  Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.supervised.instance.Resample
  Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.supervised.instance.SpreadSubsample
  Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds
  Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries
  Parses a given list of options controlling the behaviour of this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.Add
  Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.AddCluster
  Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.AddExpression
  Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.AddNoise
  Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat
  Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.ClusterMembership
  Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.Copy
  Parses a given list of options controlling the behaviour of this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.Discretize
  Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.FirstOrder
  Parses a given list of options controlling the behaviour of this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.MakeIndicator
  Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.MergeTwoValues
  Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.NominalToBinary
  Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.NumericTransform
  Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.PKIDiscretize
  Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.RandomProjection
  Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.Remove
  Parses a given list of options controlling the behaviour of this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.RemoveType
  Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.RemoveUseless
  Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.StringToNominal
  Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Parses a given list of options controlling the behaviour of this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.SwapValues
  Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.Normalize
  Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.Randomize
  Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveFolds
  Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveMisclassified
  Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemovePercentage
  Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveRange
  Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveWithValues
  Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.Resample
  Parses a list of options for this object.
setOriginalCoords(Vector) - Method in class weka.gui.beans.MetaBean
  sets the vector containing the original coordinates (instances of class Point) for the inputs
setOutput(PrintWriter) - Method in class weka.datagenerators.ClusterGenerator
  Sets the print writer.
setOutput(PrintWriter) - Method in class weka.datagenerators.Generator
  Sets the print writer.
setOutputFile(File) - Method in class weka.experiment.CrossValidationResultProducer
  Set the value of OutputFile.
setOutputFile(File) - Method in class weka.experiment.CSVResultListener
  Set the value of OutputFile.
setOutputFile(File) - Method in class weka.experiment.RandomSplitResultProducer
  Set the value of OutputFile.
setOutputFileName(String) - Method in class weka.experiment.CSVResultListener
  Set the value of OutputFileName.
setOutputFilename(String) - Method in class weka.gui.GenericPropertiesCreator
  sets the file to output the properties for the GEO to
setOutputFormatFromDialog() - Method in class weka.gui.experiment.ResultsPanel
  displays the Dialog for the output format and sets the chosen settings, if the user approves
setOutputItemSets(boolean) - Method in class weka.associations.Apriori
  Sets whether itemsets are output as well
setOutputs(Vector) - Method in class weka.gui.beans.MetaBean
setOutputWordCounts(boolean) - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Sets whether output instances contain 0 or 1 indicating word presence, or word counts.
setP(double) - Method in class weka.classifiers.BVDecomposeSegCVSub
  Set the proportion of instances that are common between two training sets used to train a classifier.
setPaint(Paint) - Method in class weka.gui.visualize.PostscriptGraphics
setPaintMode() - Method in class weka.gui.visualize.PostscriptGraphics
  Not implemented
setPanelHeight(int) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
  Set the height of the visualization
setPanelWidth(int) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
  Set the width of the visualization
SetParent(int, int) - Method in class weka.classifiers.bayes.net.ParentSet
  sets index parent of parent specified by index
setParent(Edge) - Method in class weka.gui.treevisualizer.Node
  Set the value of parent.
setParentFrame(JFrame) - Method in interface weka.gui.beans.CustomizerCloseRequester
  A reference to the parent is passed in
setParentFrame(JFrame) - Method in class weka.gui.beans.LoaderCustomizer
setParentFrame(JFrame) - Method in class weka.gui.beans.SaverCustomizer
setPassword(String) - Method in interface weka.core.converters.DatabaseConverter
setPassword(String) - Method in class weka.core.converters.DatabaseLoader
  Sets user password for the database
setPassword(String) - Method in class weka.core.converters.DatabaseSaver
  Sets the database password
setPassword(String) - Method in class weka.experiment.DatabaseUtils
  Set the database password
setPattern(int) - Method in class weka.datagenerators.BIRCHCluster
  Sets the pattern type.
setPercent(int) - Method in class weka.filters.unsupervised.attribute.AddNoise
  Sets the size of noise data, as a percentage of the original set.
setPercent(double) - Method in class weka.filters.unsupervised.attribute.RandomProjection
  Sets the percent the attributes (dimensions) of the data should be reduced to
setPercent() - Method in class weka.gui.visualize.MatrixPanel
  Calculates the percentage to resample
setPercentage(int) - Method in class weka.filters.unsupervised.instance.RemovePercentage
  Sets the percentage of intances to select.
setPercentCompleted(int) - Method in class weka.gui.boundaryvisualizer.RemoteResult
  Set the progress for this row so far
setPercentThreshold(int) - Method in class weka.attributeSelection.SVMAttributeEval
  Set the threshold below which percentage elimination reverts to constant elimination.
setPercentToEliminatePerIteration(int) - Method in class weka.attributeSelection.SVMAttributeEval
  Set the percentage of attributes to eliminate per iteration
setPixHeight(double) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
  Set the height of a pixel
setPixWidth(double) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
  Set the width of a pixel
setPlotCompanion(Plot2DCompanion) - Method in class weka.gui.visualize.Plot2D
  Set a companion class.
setPlotList(FastVector) - Method in class weka.gui.visualize.LegendPanel
  Set the list of plots to generate legend entries for
setPlotName(String) - Method in class weka.gui.visualize.PlotData2D
  Set the name of this plot
setPlotTrainingData(boolean) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel
  Set whether to superimpose the training data plot
setPlus(int, double) - Method in class weka.classifiers.functions.pace.DoubleVector
  Adds a value to an element
setPlus(int, int, double) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Add a value to an element and reset the element
setPointValue(int, double) - Method in class weka.classifiers.functions.pace.DiscreteFunction
  Sets a particular point value
setPopulationSize(int) - Method in class weka.attributeSelection.GeneticSearch
  set the population size
setPopulationSize(int) - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
setPopulationSize(int) - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
setPostProcessor(CheckClassifier.PostProcessor) - Method in class weka.classifiers.CheckClassifier
  sets the PostProcessor to use
setPredTargetColumn(boolean) - Method in class weka.experiment.ClassifierSplitEvaluator
  Set the flag for prediction and target output.
setPriors(Instances) - Method in class weka.classifiers.Evaluation
  Sets the class prior probabilities
setProduceCSV(boolean) - Method in class weka.experiment.PairedTTester
  Set whether csv is output
setProduceCSV(boolean) - Method in class weka.gui.experiment.OutputFormatDialog
  Set whether csv is output
setProduceLatex(boolean) - Method in class weka.experiment.PairedTTester
  Set whether latex is output
setProduceLatex(boolean) - Method in class weka.gui.experiment.OutputFormatDialog
  Set whether latex is output
setProperty(String, String) - Method in class weka.core.ProtectedProperties
  Overrides a method to prevent the properties from being modified.
setPropertyArray(Object) - Method in class weka.experiment.Experiment
  Sets the array of values to set the custom property to.
setPropertyArray(Object) - Method in class weka.experiment.RemoteExperiment
  Sets the array of values to set the custom property to.
setPropertyPath(PropertyNode[]) - Method in class weka.experiment.Experiment
  Sets the path of properties taken to get to the custom property to iterate over.
setPropertyPath(PropertyNode[]) - Method in class weka.experiment.RemoteExperiment
  Sets the path of properties taken to get to the custom property to iterate over.
setPruningType(SelectedTag) - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost
  Set the pruning type
setQuality(float) - Method in class weka.gui.visualize.JPEGWriter
  sets the quality the JPEG is saved in
setQuery(String) - Method in class weka.core.converters.DatabaseLoader
  Sets the query to execute against the database
setQuery(String) - Method in class weka.experiment.InstanceQuery
  Set the query to execute against the database
setRaceType(SelectedTag) - Method in class weka.attributeSelection.RaceSearch
  Set the race type
setRadiuses(String) - Method in class weka.datagenerators.BIRCHCluster
  Sets the upper and lower boundary for the radius of the clusters.
setRandom(Random) - Method in class weka.datagenerators.BIRCHCluster
  Sets the random generator.
setRandom(Random) - Method in class weka.datagenerators.RDG1
  Sets the random generator.
setRandomizeData(boolean) - Method in class weka.experiment.RandomSplitResultProducer
  Set to true if dataset is to be randomized
setRandomOrder(boolean) - Method in class weka.classifiers.bayes.net.search.global.K2
  Set random order flag
setRandomOrder(boolean) - Method in class weka.classifiers.bayes.net.search.local.K2
  Set random order flag
setRandomSeed(long) - Method in class weka.classifiers.functions.LeastMedSq
  Set the seed for the random number generator
setRandomSeed(int) - Method in class weka.classifiers.functions.SMO
  Set the value of randomSeed.
setRandomSeed(int) - Method in class weka.classifiers.trees.ADTree
  Sets random seed for a random walk.
setRandomSeed(int) - Method in class weka.filters.supervised.instance.Resample
  Sets the random number seed.
setRandomSeed(int) - Method in class weka.filters.supervised.instance.SpreadSubsample
  Sets the random number seed.
setRandomSeed(int) - Method in class weka.filters.unsupervised.attribute.AddNoise
  Sets the random number seed.
setRandomSeed(long) - Method in class weka.filters.unsupervised.attribute.RandomProjection
  Sets the random seed of the random number generator
setRandomSeed(int) - Method in class weka.filters.unsupervised.instance.Randomize
  Set the random number generator seed value.
setRandomSeed(int) - Method in class weka.filters.unsupervised.instance.Resample
  Sets the random number seed.
setRandomWidthFactor(double) - Method in class weka.classifiers.meta.MultiClassClassifier
  Sets the multiplier when generating random codes.
setRangeCorrection(SelectedTag) - Method in class weka.classifiers.meta.ThresholdSelector
  Sets the confidence range correction mode used.
setRanges(String) - Method in class weka.core.Range
  Sets the ranges from a string representation.
setRanking(boolean) - Method in class weka.attributeSelection.AttributeSelection
  produce a ranking (if possible with the set search and evaluator)
setRawOutput(boolean) - Method in class weka.experiment.CrossValidationResultProducer
  Set to true if raw split evaluator output is to be saved
setRawOutput(boolean) - Method in class weka.experiment.RandomSplitResultProducer
  Set to true if raw split evaluator output is to be saved
setReducedErrorPruning(boolean) - Method in class weka.classifiers.rules.PART
  Set the value of reducedErrorPruning.
setReducedErrorPruning(boolean) - Method in class weka.classifiers.trees.J48
  Set the value of reducedErrorPruning.
setRefer(String) - Method in class weka.gui.treevisualizer.Node
  Set the value of refer.
setRefreshFreq(int) - Method in class weka.gui.beans.StripChart
  Set how often (in x axis points) to refresh the display
setRegressionTree(boolean) - Method in class weka.classifiers.trees.m5.Rule
  Set the value of regressionTree.
setRegressionTree(boolean) - Method in class weka.classifiers.trees.m5.RuleNode
  Set the value of regressionTree.
setRelationForTableName(boolean) - Method in class weka.core.converters.DatabaseSaver
  En/Dis-ables that the relation name is used for the name of the table (default enabled).
setRelationName(String) - Method in class weka.core.Instances
  Sets the relation's name.
setRelationName(String) - Method in class weka.datagenerators.ClusterGenerator
  Sets the relation name the dataset should have.
setRelationName(String) - Method in class weka.datagenerators.Generator
  Sets the relation name the dataset should have.
setRemoteHosts(DefaultListModel) - Method in class weka.experiment.RemoteExperiment
  Set the list of remote host names
setRemoteHosts(Vector) - Method in class weka.gui.boundaryvisualizer.BoundaryPanelDistributed
  Set a list of host names of machines to distribute processing to
setRemoveAllMissingCols(boolean) - Method in class weka.associations.Apriori
  Remove columns containing all missing values.
setRenderingHint(RenderingHints.Key, Object) - Method in class weka.gui.visualize.PostscriptGraphics
setRenderingHints(Map) - Method in class weka.gui.visualize.PostscriptGraphics
setRepeatLiterals(boolean) - Method in class weka.associations.Tertius
  Set the value of repeatLiterals.
setReplaceMissingValues(boolean) - Method in class weka.filters.unsupervised.attribute.RandomProjection
  Sets either to use replace missing values filter or not
setReportFrequency(int) - Method in class weka.attributeSelection.GeneticSearch
  set how often reports are generated
setReset(boolean) - Method in class weka.classifiers.functions.MultilayerPerceptron
  This sets the network up to be able to reset itself with the current settings and the learning rate at half of what it is currently.
setReset(boolean) - Method in class weka.gui.beans.ChartEvent
  Set the reset flag
setResultKeyFromDialog() - Method in class weka.gui.experiment.ResultsPanel
setResultListener(ResultListener) - Method in class weka.experiment.AveragingResultProducer
  Sets the object to send results of each run to.
setResultListener(ResultListener) - Method in class weka.experiment.CrossValidationResultProducer
  Sets the object to send results of each run to.
setResultListener(ResultListener) - Method in class weka.experiment.DatabaseResultProducer
  Sets the object to send results of each run to.
setResultListener(ResultListener) - Method in class weka.experiment.Experiment
  Sets the result listener where results will be sent.
setResultListener(ResultListener) - Method in class weka.experiment.LearningRateResultProducer
  Sets the object to send results of each run to.
setResultListener(ResultListener) - Method in class weka.experiment.RandomSplitResultProducer
  Sets the object to send results of each run to.
setResultListener(ResultListener) - Method in class weka.experiment.RemoteExperiment
  Sets the result listener where results will be sent.
setResultListener(ResultListener) - Method in interface weka.experiment.ResultProducer
  Sets the object to send results of each run to.
setResultProducer(ResultProducer) - Method in class weka.experiment.AveragingResultProducer
  Set the ResultProducer.
setResultProducer(ResultProducer) - Method in class weka.experiment.DatabaseResultProducer
  Set the ResultProducer.
setResultProducer(ResultProducer) - Method in class weka.experiment.Experiment
  Set the result producer used for the current experiment.
setResultProducer(ResultProducer) - Method in class weka.experiment.LearningRateResultProducer
  Set the ResultProducer.
setResultProducer(ResultProducer) - Method in class weka.experiment.RemoteExperiment
  Set the result producer used for the current experiment.
setResultsetKeyColumns(Range) - Method in class weka.experiment.PairedTTester
  Set the value of ResultsetKeyColumns.
setResultsPanel(ResultsPanel) - Method in class weka.gui.experiment.RunPanel
  Sets the pointer to the results panel.
setRetrieval(int) - Method in class weka.core.converters.AbstractSaver
  Sets the retrieval mode.
setRetrieval(int) - Method in interface weka.core.converters.Saver
  Sets the retrieval mode
setRidge(double) - Method in class weka.classifiers.functions.LinearRegression
  Set the value of Ridge.
setRidge(double) - Method in class weka.classifiers.functions.Logistic
  Sets the ridge in the log-likelihood.
setRidge(double) - Method in class weka.classifiers.functions.RBFNetwork
  Sets the ridge value for logistic or linear regression.
setRocAnalysis(boolean) - Method in class weka.associations.Tertius
  Set the value of rocAnalysis.
setROCString(String) - Method in class weka.gui.visualize.ThresholdVisualizePanel
  Set the string with ROC area
setRoot(boolean) - Method in class weka.gui.treevisualizer.Node
  Set the value of root.
setRootNode(String) - Method in class weka.core.xml.XMLDocument
  sets the root node to use in the XML output.
setRow(int, double[]) - Method in class weka.core.Matrix
  Deprecated. Sets a row of the matrix to the given row.
setRowDimension(int) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Set the row dimenion of the matrix
setRowNumber(int) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
  Set the row number for this sub task
setRsource(String) - Method in class weka.gui.treevisualizer.Edge
  Set the value of rsource.
setRtarget(String) - Method in class weka.gui.treevisualizer.Edge
  Set the value of rtarget.
setRuleset(FastVector) - Method in class weka.classifiers.rules.RuleStats
  Set the ruleset of the stats, overwriting the old one if any
setRunColumn(int) - Method in class weka.experiment.PairedTTester
  Set the value of RunColumn.
setRunLower(int) - Method in class weka.experiment.Experiment
  Set the lower run number for the experiment.
setRunLower(int) - Method in class weka.experiment.RemoteExperiment
  Set the lower run number for the experiment.
setRuns(int) - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
  Sets the number of runs
setRuns(int) - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber
  Sets the number of runs
setRuns(int) - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
  Sets the m_nRuns.
setRuns(int) - Method in class weka.classifiers.bayes.net.search.global.TabuSearch
  Sets the number of runs
setRuns(int) - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
  Sets the number of runs
setRuns(int) - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber
  Sets the number of runs
setRuns(int) - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
  Sets the m_nRuns.
setRuns(int) - Method in class weka.classifiers.bayes.net.search.local.TabuSearch
  Sets the number of runs
setRunUpper(int) - Method in class weka.experiment.Experiment
  Set the upper run number for the experiment.
setRunUpper(int) - Method in class weka.experiment.RemoteExperiment
  Set the upper run number for the experiment.
setSampleSize(int) - Method in class weka.attributeSelection.ReliefFAttributeEval
  Set the number of instances to sample for attribute estimation
setSampleSize(int) - Method in class weka.classifiers.functions.LeastMedSq
  sets number of samples
setSampleSizePercent(double) - Method in class weka.filters.supervised.instance.Resample
  Sets the size of the subsample, as a percentage of the original set.
setSampleSizePercent(double) - Method in class weka.filters.unsupervised.instance.Resample
  Sets the size of the subsample, as a percentage of the original set.
setSaveDialogTitle(String) - Method in class weka.gui.visualize.PrintableComponent
  sets the title for the save dialog
setSaveDialogTitle(String) - Method in interface weka.gui.visualize.PrintableHandler
  sets the title for the save dialog
setSaveDialogTitle(String) - Method in class weka.gui.visualize.PrintablePanel
  sets the title for the save dialog
setSaveInstanceData(boolean) - Method in class weka.classifiers.trees.ADTree
  Sets whether the tree is to save instance data.
setSaveInstanceData(boolean) - Method in class weka.classifiers.trees.J48
  Set whether instance data is to be saved.
setSaveInstanceData(boolean) - Method in class weka.clusterers.Cobweb
  Set the value of saveInstances.
setSaveInstances(boolean) - Method in class weka.classifiers.trees.M5P
  Set whether to save instance data at each node in the tree for visualization purposes
setSaver(Saver) - Method in class weka.gui.beans.Saver
  Set the loader to use
setScale(double, double) - Method in class weka.gui.visualize.JComponentWriter
  sets the scale factor - is ignored since we always create a screenshot!
setScale(double, double) - Method in class weka.gui.visualize.PrintableComponent
  sets the scale factor
setScale(double, double) - Method in interface weka.gui.visualize.PrintableHandler
  sets the scale factor
setScale(double, double) - Method in class weka.gui.visualize.PrintablePanel
  sets the scale factor
setScalingEnabled(boolean) - Method in class weka.gui.visualize.JComponentWriter
  sets whether to enable scaling
setScoreType(SelectedTag) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
  set quality measure to be used in searching for networks.
setSearch(ASSearch) - Method in class weka.attributeSelection.AttributeSelection
  set the search method
setSearch(ASSearch) - Method in class weka.classifiers.meta.AttributeSelectedClassifier
  Sets the search method
setSearch(ASSearch) - Method in class weka.filters.supervised.attribute.AttributeSelection
  Set as string holding the name of a search class
setSearchAlgorithm(SearchAlgorithm) - Method in class weka.classifiers.bayes.BayesNet
  Set the SearchAlgorithm used in searching for network structures.
setSearchBackwards(boolean) - Method in class weka.attributeSelection.GreedyStepwise
  Set whether to search backwards instead of forwards
setSearchPath(SelectedTag) - Method in class weka.classifiers.trees.ADTree
  Sets the method of searching the tree for a new insertion.
setSearchPercent(double) - Method in class weka.attributeSelection.RandomSearch
  set the percentage of the search space to consider
setSearchString(String) - Method in class weka.gui.arffviewer.ArffTable
  sets the search string to look for in the table, NULL or "" disables the search
setSearchTermination(int) - Method in class weka.attributeSelection.BestFirst
  Set the numnber of non-improving nodes to consider before terminating search.
setSecondValueIndex(String) - Method in class weka.filters.unsupervised.attribute.MergeTwoValues
  Sets index of the second value used.
setSecondValueIndex(String) - Method in class weka.filters.unsupervised.attribute.SwapValues
  Sets index of the second value used.
setSeed(int) - Method in class weka.attributeSelection.AttributeSelection
  set the seed for use in cross validation
setSeed(int) - Method in class weka.attributeSelection.GeneticSearch
  set the seed for random number generation
setSeed(int) - Method in class weka.attributeSelection.OneRAttributeEval
  Set the random number seed for cross validation
setSeed(int) - Method in class weka.attributeSelection.ReliefFAttributeEval
  Set the random number seed for randomly sampling instances.
setSeed(int) - Method in class weka.attributeSelection.WrapperSubsetEval
  Set the seed to use for cross validation
setSeed(int) - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
  Sets the random number seed
setSeed(int) - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber
  Sets the random number seed
setSeed(int) - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
  Sets the random number seed
setSeed(int) - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
  Sets the random number seed
setSeed(int) - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber
  Sets the random number seed
setSeed(int) - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
  Sets the random number seed
setSeed(int) - Method in class weka.classifiers.BVDecompose
  Sets the random number seed
setSeed(int) - Method in class weka.classifiers.BVDecomposeSegCVSub
  Sets the random number seed
setSeed(int) - Method in class weka.classifiers.evaluation.EvaluationUtils
  Sets the seed for randomization during cross-validation
setSeed(int) - Method in class weka.classifiers.functions.MultilayerPerceptron
  This seeds the random number generator, that is used when a random number is needed for the network.
setSeed(int) - Method in class weka.classifiers.functions.VotedPerceptron
  Set the value of Seed.
setSeed(int) - Method in class weka.classifiers.functions.Winnow
  Set the value of Seed.
setSeed(int) - Method in class weka.classifiers.meta.MultiScheme
  Sets the seed for random number generation.
setSeed(int) - Method in class weka.classifiers.RandomizableClassifier
  Set the seed for random number generation.
setSeed(int) - Method in class weka.classifiers.RandomizableIteratedSingleClassifierEnhancer
  Set the seed for random number generation.
setSeed(int) - Method in class weka.classifiers.RandomizableMultipleClassifiersCombiner
  Set the seed for random number generation.
setSeed(int) - Method in class weka.classifiers.RandomizableSingleClassifierEnhancer
  Set the seed for random number generation.
setSeed(long) - Method in class weka.classifiers.rules.ConjunctiveRule
setSeed(long) - Method in class weka.classifiers.rules.JRip
setSeed(int) - Method in class weka.classifiers.rules.PART
  Set the value of Seed.
setSeed(int) - Method in class weka.classifiers.rules.Ridor
setSeed(int) - Method in class weka.classifiers.trees.J48
  Set the value of Seed.
setSeed(int) - Method in class weka.classifiers.trees.RandomForest
  Set the seed for random number generation.
setSeed(int) - Method in class weka.classifiers.trees.RandomTree
  Set the seed for random number generation.
setSeed(int) - Method in class weka.classifiers.trees.REPTree
  Set the value of Seed.
setSeed(int) - Method in class weka.clusterers.EM
  Set the random number seed
setSeed(int) - Method in class weka.clusterers.FarthestFirst
  Set the random number seed
setSeed(int) - Method in class weka.clusterers.SimpleKMeans
  Set the random number seed
setSeed(int) - Method in interface weka.core.Randomizable
  Set the seed for random number generation.
setSeed(int) - Method in class weka.datagenerators.BIRCHCluster
  Sets the random number seed.
setSeed(int) - Method in class weka.datagenerators.RDG1
  Sets the random number seed.
setSeed(long) - Method in class weka.filters.supervised.attribute.ClassOrder
  Set randomization seed
setSeed(long) - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds
  Sets the random number seed for shuffling the dataset.
setSeed(long) - Method in class weka.filters.unsupervised.instance.RemoveFolds
  Sets the random number seed for shuffling the dataset.
setSeed(int) - Method in class weka.gui.beans.CrossValidationFoldMaker
  Set the seed
setSeed(int) - Method in class weka.gui.beans.TrainTestSplitMaker
  Set the random seed
setSeed(int) - Method in interface weka.gui.boundaryvisualizer.DataGenerator
  Set a seed for random number generation (if needed).
setSeed(int) - Method in class weka.gui.boundaryvisualizer.KDDataGenerator
  Initializes a new random number generator using the supplied seed.
setSelectedColumn(int) - Method in class weka.gui.arffviewer.ArffTable
  sets the selected column
setSelectedRange(String) - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Set the value of m_SelectedRange.
setSelectionThreshold(double) - Method in class weka.attributeSelection.RaceSearch
  Set the threshold by which the AttributeSelection module can discard attributes.
setSeparatingThreshold(double) - Method in class weka.classifiers.functions.pace.ChisqMixture
  Sets the separating threshold value
setSeparatingThreshold(double) - Method in class weka.classifiers.functions.pace.NormalMixture
  Sets the separating threshold value
setSeperator(String) - Method in class weka.gui.HierarchyPropertyParser
  Set the seperator between levels.
setSequentialAttIndex(boolean) - Method in class weka.classifiers.lazy.LBR.Indexes
  A Sequential Attribute index is all those Attributes that are set to the specified value placed in a sequential array.
setSequentialDataset(boolean) - Method in class weka.classifiers.lazy.LBR.Indexes
  Sets both the Instance and Attribute indexes to a specified value
setSequentialInstanceIndex(boolean) - Method in class weka.classifiers.lazy.LBR.Indexes
  A Sequential Instance index is all those Instances that are set to the specified value placed in a sequential array.
setShape(int) - Method in class weka.gui.treevisualizer.Node
  Set the value of shape.
setShapes(FastVector) - Method in class weka.gui.visualize.VisualizePanel
  This will set the shapes for the instances.
setShapeSize(int[]) - Method in class weka.gui.visualize.PlotData2D
  Set the shape sizes for the plot data
setShapeSize(FastVector) - Method in class weka.gui.visualize.PlotData2D
  Set the shape sizes for the plot data
setShapeType(int[]) - Method in class weka.gui.visualize.PlotData2D
  Set the shape type for the plot data
setShapeType(FastVector) - Method in class weka.gui.visualize.PlotData2D
  Set the shape type for the plot data
setShowStdDevs(boolean) - Method in class weka.experiment.PairedTTester
  Set whether standard deviations are displayed or not.
setShrinkage(double) - Method in class weka.classifiers.meta.AdditiveRegression
  Set the shrinkage parameter
setShrinkage(double) - Method in class weka.classifiers.meta.LogitBoost
  Set the value of Shrinkage.
setShuffle(int) - Method in class weka.classifiers.rules.Ridor
setSigma(int) - Method in class weka.attributeSelection.ReliefFAttributeEval
  Sets the sigma value.
setSignificanceLevel(double) - Method in class weka.associations.Apriori
  Set the value of significanceLevel.
setSignificanceLevel(double) - Method in class weka.attributeSelection.RaceSearch
  Sets the significance level to use
setSignificanceLevel(double) - Method in class weka.experiment.PairedTTester
  Set the value of SignificanceLevel.
setSilent(boolean) - Method in class weka.classifiers.CheckClassifier
  Set slient mode, i.e., no output at all to stdout
setSIndex(int) - Method in class weka.gui.visualize.VisualizePanel
  Set the shape for creating splits.
setSingle(String) - Method in class weka.gui.ResultHistoryPanel
  Sets the single-click display to view the named result.
setSingleIndex(String) - Method in class weka.core.SingleIndex
  Sets the index from a string representation.
setSize(int) - Method in class weka.classifiers.functions.pace.DoubleVector
  Sets the size of the vector
setSize(int) - Method in class weka.classifiers.functions.pace.IntVector
  Sets the size of the vector.
setSmoothing(boolean) - Method in class weka.classifiers.trees.m5.Rule
  Smooth predictions
setSmoothingParameter(double) - Method in class weka.classifiers.bayes.ComplementNaiveBayes
  Sets the smoothing value used to avoid zero WordGivenClass probabilities
setSource(File) - Method in class weka.core.converters.AbstractLoader
  Default implementation throws an IOException.
setSource(InputStream) - Method in class weka.core.converters.AbstractLoader
  Default implementation throws an IOException.
setSource(File) - Method in class weka.core.converters.ArffLoader
  Resets the Loader object and sets the source of the data set to be the supplied File object.
setSource(InputStream) - Method in class weka.core.converters.ArffLoader
  Resets the Loader object and sets the source of the data set to be the supplied InputStream.
setSource(File) - Method in class weka.core.converters.C45Loader
  Resets the Loader object and sets the source of the data set to be the supplied File object.
setSource(File) - Method in class weka.core.converters.CSVLoader
  Resets the Loader object and sets the source of the data set to be the supplied File object.
setSource(String, String, String) - Method in class weka.core.converters.DatabaseLoader
  Sets the database url
setSource(String) - Method in class weka.core.converters.DatabaseLoader
  Sets the database url
setSource() - Method in class weka.core.converters.DatabaseLoader
  Sets the database url using the DatabaseUtils file
setSource(File) - Method in interface weka.core.converters.Loader
  Resets the Loader object and sets the source of the data set to be the supplied File object.
setSource(InputStream) - Method in interface weka.core.converters.Loader
  Resets the Loader object and sets the source of the data set to be the supplied InputStream.
setSource(File) - Method in class weka.core.converters.SerializedInstancesLoader
  Resets the Loader object and sets the source of the data set to be the supplied File object.
setSource(InputStream) - Method in class weka.core.converters.SerializedInstancesLoader
  Resets the Loader object and sets the source of the data set to be the supplied InputStream.
setSource(Node) - Method in class weka.gui.treevisualizer.Edge
  Set the value of source.
setSparseData(boolean) - Method in class weka.experiment.InstanceQuery
  Sets whether data should be encoded as sparse instances
setSplitByDataSet(boolean) - Method in class weka.experiment.RemoteExperiment
  Set whether sub experiments are to be created on the basis of data set.
setSplitEvaluator(SplitEvaluator) - Method in class weka.experiment.CrossValidationResultProducer
  Set the SplitEvaluator.
setSplitEvaluator(SplitEvaluator) - Method in class weka.experiment.RandomSplitResultProducer
  Set the SplitEvaluator.
setSplitOnResiduals(boolean) - Method in class weka.classifiers.trees.LMT
  Set the value of splitOnResiduals.
setSplitPoint(Instances) - Method in class weka.classifiers.trees.j48.BinC45Split
  Sets split point to greatest value in given data smaller or equal to old split point.
setSplitPoint(Instances) - Method in class weka.classifiers.trees.j48.C45Split
  Sets split point to greatest value in given data smaller or equal to old split point.
setSplitPoint(double) - Method in class weka.filters.unsupervised.instance.RemoveWithValues
  Split point to be used for selection on numeric attribute.
setStartSet(String) - Method in class weka.attributeSelection.BestFirst
  Sets a starting set of attributes for the search.
setStartSet(String) - Method in class weka.attributeSelection.GeneticSearch
  Sets a starting set of attributes for the search.
setStartSet(String) - Method in class weka.attributeSelection.GreedyStepwise
  Sets a starting set of attributes for the search.
setStartSet(String) - Method in class weka.attributeSelection.RandomSearch
  Sets a starting set of attributes for the search.
setStartSet(String) - Method in class weka.attributeSelection.Ranker
  Sets a starting set of attributes for the search.
setStartSet(String) - Method in interface weka.attributeSelection.StartSetHandler
  Sets a starting set of attributes for the search.
setStatic() - Method in class weka.gui.beans.BeanVisual
  Set the static version of the icon
setStatus(int) - Method in class weka.gui.beans.IncrementalClassifierEvent
  Set the status
setStatus(int) - Method in class weka.gui.beans.InstanceEvent
  Set the status
setStatusMessage(String) - Method in class weka.experiment.TaskStatusInfo
  Set the status message.
setStdDevPrec(int) - Method in class weka.experiment.PairedTTester
  Sets the precision of the std.
setStdDevPrec(int) - Method in class weka.gui.experiment.OutputFormatDialog
  Sets the precision of the std.
setStepSize(int) - Method in class weka.experiment.LearningRateResultProducer
  Set the value of StepSize.
setStroke(Stroke) - Method in class weka.gui.visualize.PostscriptGraphics
setStructure(Instances) - Method in class weka.core.converters.AbstractSaver
  Sets the strcuture of the instances for the first step of incremental saving.
setStructure(Instances) - Method in class weka.gui.beans.IncrementalClassifierEvent
  Set the instances structure
setStructure(Instances) - Method in class weka.gui.beans.InstanceEvent
  Set the instances structure
setSubFlow(Vector) - Method in class weka.gui.beans.MetaBean
setSubtreeRaising(boolean) - Method in class weka.classifiers.trees.J48
  Set the value of subtreeRaising.
setSuppressErrorMessage(boolean) - Method in class weka.classifiers.functions.SimpleLinearRegression
  Turn off the error message that is reported when no useful attribute is found.
setTableName(String) - Method in class weka.core.converters.DatabaseSaver
  Sets the table's name
setTabuList(int) - Method in class weka.classifiers.bayes.net.search.global.TabuSearch
  Sets the Tabu List length.
setTabuList(int) - Method in class weka.classifiers.bayes.net.search.local.TabuSearch
  Sets the Tabu List length.
setTarget(Object) - Method in class weka.gui.PropertySheetPanel
  Sets a new target object for customisation.
setTarget(Node) - Method in class weka.gui.treevisualizer.Edge
  Set the value of target.
setTaskResult(Object) - Method in class weka.experiment.TaskStatusInfo
  Set the returnable result for this task..
setTestBaseFromDialog() - Method in class weka.gui.experiment.ResultsPanel
setText(String) - Method in class weka.gui.beans.BeanVisual
  Set the label for the visual.
setTFTransform(boolean) - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Sets whether if the word frequencies should be transformed into log(1+fij) where fij is the frequency of word i in document(instance) j.
setThreshold(double) - Method in class weka.attributeSelection.GreedyStepwise
  Set the threshold by which the AttributeSelection module can discard attributes.
setThreshold(double) - Method in class weka.attributeSelection.RaceSearch
  Sets the threshold for comparisons
setThreshold(double) - Method in interface weka.attributeSelection.RankedOutputSearch
  Sets a threshold by which attributes can be discarded from the ranking.
setThreshold(double) - Method in class weka.attributeSelection.Ranker
  Set the threshold by which the AttributeSelection module can discard attributes.
setThreshold(double) - Method in class weka.attributeSelection.WrapperSubsetEval
  Set the value of the threshold for repeating cross validation
setThreshold(double) - Method in class weka.classifiers.functions.PaceRegression
  Set threshold for the olsc estimator
setThreshold(double) - Method in class weka.classifiers.functions.Winnow
  Set the value of Threshold.
setThreshold(double) - Method in class weka.filters.unsupervised.instance.RemoveMisclassified
  Sets the threshold for the max error when predicting a numeric class.
setTimes(int, double) - Method in class weka.classifiers.functions.pace.DoubleVector
  Multiplies a value to an element
setTimes(int, int, double) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Multiply a value with an element and reset the element
setToleranceParameter(double) - Method in class weka.attributeSelection.SVMAttributeEval
  Set the value of T for SMO
setToleranceParameter(double) - Method in class weka.classifiers.functions.SMO
  Set the value of tolerance parameter.
setToleranceParameter(double) - Method in class weka.classifiers.functions.SMOreg
  Set the value of tolerance parameter.
setTop(double) - Method in class weka.gui.treevisualizer.Node
  Set the value of top.
setTrainingData(Instances) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel
  Set the training data to use
setTrainingTime(int) - Method in class weka.classifiers.functions.MultilayerPerceptron
  Set the number of training epochs to perform.
setTrainIterations(int) - Method in class weka.classifiers.BVDecompose
  Sets the maximum number of boost iterations
setTrainPercent(double) - Method in class weka.experiment.RandomSplitResultProducer
  Set the value of TrainPercent.
setTrainPercent(int) - Method in class weka.gui.beans.TrainTestSplitMaker
  Set the percentage of data to be in the training portion of the split
setTrainPoolSize(int) - Method in class weka.classifiers.BVDecompose
  Set the number of instances in the training pool.
setTrainSize(int) - Method in class weka.classifiers.BVDecomposeSegCVSub
  Set the training size.
setTransform(AffineTransform) - Method in class weka.gui.visualize.PostscriptGraphics
setTransformAllValues(boolean) - Method in class weka.filters.supervised.attribute.NominalToBinary
  Sets whether all nominal values are transformed into new attributes, not just if there are more than 2.
setTransformBackToOriginal(boolean) - Method in class weka.attributeSelection.PrincipalComponents
  Sets whether the data should be transformed back to the original space
setTrimingThreshold(double) - Method in class weka.classifiers.functions.pace.ChisqMixture
  Sets the triming thresholding value.
setTrimingThreshold(double) - Method in class weka.classifiers.functions.pace.NormalMixture
  Sets the triming thresholding value.
setTrueNegative(double) - Method in class weka.classifiers.evaluation.TwoClassStats
  Sets the number of negative instances predicted as negative
setTruePositive(double) - Method in class weka.classifiers.evaluation.TwoClassStats
  Sets the number of positive instances predicted as positive
setTStart(double) - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
  Sets the m_fTStart.
setTStart(double) - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
  Sets the m_fTStart.
setType(int) - Method in class weka.classifiers.functions.neural.NeuralConnection
setUndoEnabled(boolean) - Method in interface weka.core.Undoable
  sets whether undo support is enabled
setUndoEnabled(boolean) - Method in class weka.gui.arffviewer.ArffPanel
  sets whether undo support is enabled
setUndoEnabled(boolean) - Method in class weka.gui.arffviewer.ArffTableModel
  sets whether undo support is enabled
setUndoEnabled(boolean) - Method in class weka.gui.arffviewer.ArffTableSorter
  sets whether undo support is enabled
setUnpruned(boolean) - Method in class weka.classifiers.rules.PART
  Set the value of unpruned.
setUnpruned(boolean) - Method in class weka.classifiers.trees.J48
  Set the value of unpruned.
setUnpruned(boolean) - Method in class weka.classifiers.trees.m5.M5Base
  Use unpruned tree/rules
setUnpruned(boolean) - Method in class weka.classifiers.trees.m5.Rule
  Use unpruned tree/rules
setupAttribLists() - Method in class weka.gui.visualize.MatrixPanel
  Sets up the UI's attributes lists
setUpComboBoxes(Instances) - Method in class weka.gui.visualize.ThresholdVisualizePanel
  This overloads VisualizePanel's setUpComboBoxes to add ActionListeners to watch for when the X/Y Axis comboboxes are changed.
setUpComboBoxes(Instances) - Method in class weka.gui.visualize.VisualizePanel
setUpdateIncrementalClassifier(boolean) - Method in class weka.gui.beans.Classifier
setUpFile() - Method in class weka.gui.beans.LoaderCustomizer
setUpFile() - Method in class weka.gui.beans.SaverCustomizer
  Sets up dialog for saving instances in a file
SetupModePanel - Class in weka.gui.experiment
  This panel switches between simple and advanced experiment setup panels.
SetupModePanel() - Constructor for class weka.gui.experiment.SetupModePanel
  Creates the setup panel with no initial experiment.
SetupPanel - Class in weka.gui.experiment
  This panel controls the configuration of an experiment.
SetupPanel(Experiment) - Constructor for class weka.gui.experiment.SetupPanel
  Creates the setup panel with the supplied initial experiment.
SetupPanel() - Constructor for class weka.gui.experiment.SetupPanel
  Creates the setup panel with no initial experiment.
setUpper(int) - Method in class weka.core.Range
  Sets the value of "last".
setUpper(int) - Method in class weka.core.SingleIndex
  Sets the value of "last".
setUpperBoundMinSupport(double) - Method in class weka.associations.Apriori
  Set the value of upperBoundMinSupport.
setUpperSize(int) - Method in class weka.experiment.LearningRateResultProducer
  Set the value of UpperSize.
setUpVisualizableInstances(Instances) - Static method in class weka.gui.explorer.ClassifierPanel
  Sets up the structure for the visualizable instances.
setUpVisualizableInstances(Instances, ClusterEvaluation) - Static method in class weka.gui.explorer.ClustererPanel
  Sets up the structure for the visualizable instances.
setUrl(String) - Method in interface weka.core.converters.DatabaseConverter
setUrl(String) - Method in class weka.core.converters.DatabaseLoader
  Sets the database URL
setUrl(String) - Method in class weka.core.converters.DatabaseSaver
  Sets the database URL
setUseADTree(boolean) - Method in class weka.classifiers.bayes.BayesNet
  Set whether ADTree structure is used or not
setUseArcReversal(boolean) - Method in class weka.classifiers.bayes.net.search.global.HillClimber
  set use the arc reversal operation
setUseArcReversal(boolean) - Method in class weka.classifiers.bayes.net.search.local.HillClimber
  set use the arc reversal operation
setUseBetterEncoding(boolean) - Method in class weka.filters.supervised.attribute.Discretize
  Sets whether better encoding is to be used for MDL.
setUseCrossOver(boolean) - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
setUseCrossOver(boolean) - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
setUseCrossValidation(boolean) - Method in class weka.classifiers.functions.SimpleLogistic
  Set the value of useCrossValidation.
setUseEqualFrequency(boolean) - Method in class weka.filters.unsupervised.attribute.Discretize
  Set the value of UseEqualFrequency.
setUseEqualFrequency(boolean) - Method in class weka.filters.unsupervised.attribute.PKIDiscretize
  Set the value of UseEqualFrequency.
setUseIBk(boolean) - Method in class weka.classifiers.rules.DecisionTable
  Sets whether IBk should be used instead of the majority class
setUseK2Prior(boolean) - Method in class weka.classifiers.bayes.net.estimate.BMAEstimator
  Sets the UseK2Prior.
setUseK2Prior(boolean) - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator
  Sets the UseK2Prior.
setUseKernelEstimator(boolean) - Method in class weka.classifiers.bayes.NaiveBayes
  Sets if kernel estimator is to be used.
setUseKononenko(boolean) - Method in class weka.filters.supervised.attribute.Discretize
  Sets whether Kononenko's MDL criterion is to be used.
setUseLaplace(boolean) - Method in class weka.classifiers.trees.J48
  Set the value of useLaplace.
setUseMissing(boolean) - Method in class weka.filters.unsupervised.attribute.AddNoise
  Sets the flag if missing values are treated as extra values.
setUseMutation(boolean) - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
setUseMutation(boolean) - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
setUseProb(boolean) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
setUsePropertyIterator(boolean) - Method in class weka.experiment.Experiment
  Sets whether the custom property iterator should be used.
setUsePropertyIterator(boolean) - Method in class weka.experiment.RemoteExperiment
  Sets whether the custom property iterator should be used.
setUsePruning(boolean) - Method in class weka.classifiers.rules.JRip
setUser(String) - Method in interface weka.core.converters.DatabaseConverter
setUser(String) - Method in class weka.core.converters.DatabaseLoader
  Sets the database user
setUser(String) - Method in class weka.core.converters.DatabaseSaver
  Sets the database user
setUseRBF(boolean) - Method in class weka.classifiers.functions.SMO
  Set if the RBF kernel is to be used.
setUseRBF(boolean) - Method in class weka.classifiers.functions.SMOreg
  Set if the RBF kernel is to be used.
setUseResampling(boolean) - Method in class weka.classifiers.meta.AdaBoostM1
  Set resampling mode
setUseResampling(boolean) - Method in class weka.classifiers.meta.LogitBoost
  Set resampling mode
setUseResampling(boolean) - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost
  Set resampling mode
setUsername(String) - Method in class weka.experiment.DatabaseUtils
  Set the database username
setUseStoplist(boolean) - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Sets whether if the words that are on a stoplist are to be ignored (The stop list is in weka.core.StopWords).
setUseSupervisedDiscretization(boolean) - Method in class weka.classifiers.bayes.NaiveBayes
  Set whether supervised discretization is to be used.
setUseSupervisedDiscretization(boolean) - Method in class weka.classifiers.bayes.NaiveBayesUpdateable
  Set whether supervised discretization is to be used.
setUseTournamentSelection(boolean) - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
setUseTournamentSelection(boolean) - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
setUseTraining(boolean) - Method in class weka.attributeSelection.ClassifierSubsetEval
  Set if training data is to be used instead of hold out/test data
setUseTree(boolean) - Method in class weka.classifiers.trees.m5.Rule
  Use an m5 tree rather than generate rules
setUseUnsmoothed(boolean) - Method in class weka.classifiers.trees.m5.M5Base
  Use unsmoothed predictions
setValidating(boolean) - Method in class weka.core.xml.XMLDocument
  sets whether to use a validating parser or not.
  Note: this does clear the current DOM document!
setValidating(boolean) - Method in class weka.core.xml.XMLOptions
  sets whether to use a validating parser or not.
setValidationChunkSize(int) - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost
  Set the validation chunk size
setValidationSetSize(int) - Method in class weka.classifiers.functions.MultilayerPerceptron
  This will set the size of the validation set.
setValidationThreshold(int) - Method in class weka.classifiers.functions.MultilayerPerceptron
  This sets the threshold to use for when validation testing is being done.
setValue(double) - Method in class weka.classifiers.trees.adtree.PredictionNode
  Sets the prediction value of the node.
setValue(int, double) - Method in class weka.core.BinarySparseInstance
  Sets a specific value in the instance to the given value (internal floating-point format).
setValue(int, double) - Method in class weka.core.Instance
  Sets a specific value in the instance to the given value (internal floating-point format).
setValue(int, String) - Method in class weka.core.Instance
  Sets a value of a nominal or string attribute to the given value.
setValue(Attribute, double) - Method in class weka.core.Instance
  Sets a specific value in the instance to the given value (internal floating-point format).
setValue(Attribute, String) - Method in class weka.core.Instance
  Sets a value of an nominal or string attribute to the given value.
setValue(int, double) - Method in class weka.core.SparseInstance
  Sets a specific value in the instance to the given value (internal floating-point format).
setValue(Object) - Method in class weka.gui.CostMatrixEditor
  Sets the value of the CostMatrix to be edited.
setValue(Object) - Method in class weka.gui.GenericArrayEditor
  Sets the current object array.
setValue(Object) - Method in class weka.gui.GenericObjectEditor
  Sets the current Object.
setValue(Object) - Method in class weka.gui.SimpleDateFormatEditor
  Sets the value of the date format to be edited.
setValueAt(Object, int, int) - Method in class weka.gui.arffviewer.ArffTableModel
  sets the value in the cell at columnIndex and rowIndex to aValue.
setValueAt(Object, int, int, boolean) - Method in class weka.gui.arffviewer.ArffTableModel
  sets the value in the cell at columnIndex and rowIndex to aValue.
setValueAt(Object, int, int) - Method in class weka.gui.TableMap
setValueAt(Object, int, int) - Method in class weka.gui.TableSorter
setValueIndex(int) - Method in class weka.filters.unsupervised.attribute.MakeIndicator
  Sets index of the indicator value.
setValueIndices(String) - Method in class weka.filters.unsupervised.attribute.MakeIndicator
  Sets indices of the indicator values.
setValueIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.MakeIndicator
  Set which attributes are to be deleted (or kept if invert is true)
setValuesOutput(SelectedTag) - Method in class weka.associations.Tertius
  Set the value of valuesOutput.
setValueSparse(int, double) - Method in class weka.core.BinarySparseInstance
  Sets a specific value in the instance to the given value (internal floating-point format).
setValueSparse(int, double) - Method in class weka.core.Instance
  Sets a specific value in the instance to the given value (internal floating-point format).
setValueSparse(int, double) - Method in class weka.core.SparseInstance
  Sets a specific value in the instance to the given value (internal floating-point format).
setVarianceCovered(double) - Method in class weka.attributeSelection.PrincipalComponents
  Sets the amount of variance to account for when retaining principal components
setVerbose(boolean) - Method in class weka.associations.Apriori
  Sets verbose mode
setVerbose(boolean) - Method in class weka.attributeSelection.ExhaustiveSearch
  set whether or not to output new best subsets as the search proceeds
setVerbose(boolean) - Method in class weka.attributeSelection.RandomSearch
  set whether or not to output new best subsets as the search proceeds
setVisual(BeanVisual) - Method in class weka.gui.beans.AbstractDataSink
  Set the visual for this data source
setVisual(BeanVisual) - Method in class weka.gui.beans.AbstractDataSource
  Set the visual for this data source
setVisual(BeanVisual) - Method in class weka.gui.beans.AbstractEvaluator
  Set the visual
setVisual(BeanVisual) - Method in class weka.gui.beans.AbstractTestSetProducer
  Set the visual for this bean
setVisual(BeanVisual) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer
  Set the visual for this bean
setVisual(BeanVisual) - Method in class weka.gui.beans.AbstractTrainingSetProducer
  Set the visual for this bean
setVisual(BeanVisual) - Method in class weka.gui.beans.ClassAssigner
setVisual(BeanVisual) - Method in class weka.gui.beans.Classifier
  Sets the visual appearance of this wrapper bean
setVisual(BeanVisual) - Method in class weka.gui.beans.ClassValuePicker
setVisual(BeanVisual) - Method in class weka.gui.beans.Clusterer
  Sets the visual appearance of this wrapper bean
setVisual(BeanVisual) - Method in class weka.gui.beans.DataVisualizer
  Set the visual appearance of this bean
setVisual(BeanVisual) - Method in class weka.gui.beans.Filter
  Set the visual appearance of this bean
setVisual(BeanVisual) - Method in class weka.gui.beans.GraphViewer
  Set the visual appearance of this bean
setVisual(BeanVisual) - Method in class weka.gui.beans.MetaBean
  Sets the visual appearance of this wrapper bean
setVisual(BeanVisual) - Method in class weka.gui.beans.ModelPerformanceChart
  Set the visual appearance of this bean
setVisual(BeanVisual) - Method in class weka.gui.beans.PredictionAppender
  Set the visual for this data source
setVisual(BeanVisual) - Method in class weka.gui.beans.StripChart
  Set the visual appearance of this bean
setVisual(BeanVisual) - Method in class weka.gui.beans.TextViewer
  Describe `setVisual` method here.
setVisual(BeanVisual) - Method in interface weka.gui.beans.Visible
  Set a new visual representation
setVoteFlag(boolean) - Method in class weka.datagenerators.RDG1
  Sets the vote flag.
setWeight(double) - Method in class weka.core.Instance
  Sets the weight of an instance.
setWeightByConfidence(boolean) - Method in class weka.classifiers.misc.VFI
  Set weighting by confidence
setWeightByDistance(boolean) - Method in class weka.attributeSelection.ReliefFAttributeEval
  Set the nearest neighbour weighting method
setWeightingDimensions(boolean[]) - Method in interface weka.gui.boundaryvisualizer.DataGenerator
  Set the dimensions to be used in computing a weight for each instance generated
setWeightingDimensions(boolean[]) - Method in class weka.gui.boundaryvisualizer.KDDataGenerator
  Set which dimensions to use when computing a weight for the next instance to generate
setWeightingKernel(int) - Method in class weka.classifiers.lazy.LWL
  Sets the kernel weighting method to use.
setWeightingValues(double[]) - Method in interface weka.gui.boundaryvisualizer.DataGenerator
  Set the values of the dimensions (chosen via setWeightingDimensions) to be used when computing instance weights
setWeightingValues(double[]) - Method in class weka.gui.boundaryvisualizer.KDDataGenerator
  Set the values for the weighting dimensions to be used when computing the weight for the next instance to be generated
setWeightThreshold(int) - Method in class weka.classifiers.meta.AdaBoostM1
  Set weight threshold
setWeightThreshold(int) - Method in class weka.classifiers.meta.LogitBoost
  Set weight thresholding
setWholeDataErr(boolean) - Method in class weka.classifiers.rules.Ridor
setWindowSize(int) - Method in class weka.classifiers.lazy.IBk
  Sets the maximum number of instances allowed in the training pool.
setWordsToKeep(int) - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Sets the number of words (per class if there is a class attribute assigned) to attempt to keep.
setWrappedAlgorithm(Object) - Method in class weka.gui.beans.Classifier
  Sets the algorithm (classifier) for this bean
setWrappedAlgorithm(Object) - Method in class weka.gui.beans.Clusterer
  Sets the algorithm (clusterer) for this bean
setWrappedAlgorithm(Object) - Method in class weka.gui.beans.Filter
  Set the filter to be wrapped by this bean
setWrappedAlgorithm(Object) - Method in class weka.gui.beans.Loader
  Set the loader
setWrappedAlgorithm(Object) - Method in class weka.gui.beans.Saver
  Set the saver
setWrappedAlgorithm(Object) - Method in interface weka.gui.beans.WekaWrapper
  Set the algorithm.
setX(double) - Method in class weka.classifiers.functions.neural.NeuralConnection
setX(int) - Method in class weka.gui.beans.BeanInstance
  Sets the x coordinate of this bean
setX(int) - Method in class weka.gui.visualize.AttributePanel
  shows which bar is the current x attribute.
setXAttribute(int) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel
  Set the x attribute index
setXAttribute(int) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
  Set the x axis fixed dimension
setXindex(int) - Method in class weka.gui.visualize.Plot2D
  Set the index of the attribute to go on the x axis
setXindex(int) - Method in class weka.gui.visualize.PlotData2D
  Set the x index of the data.
setXIndex(int) - Method in class weka.gui.visualize.VisualizePanel
  Set the index of the attribute for the x axis
setXLabelFreq(int) - Method in class weka.gui.beans.StripChart
  Set the frequency for printing x label values
setXORMode(Color) - Method in class weka.gui.visualize.PostscriptGraphics
  Not implemented
setXval(boolean) - Method in class weka.attributeSelection.AttributeSelection
  do a cross validation
setXY(int, int) - Method in class weka.gui.beans.BeanInstance
  Set the x and y coordinates of this bean
setY(double) - Method in class weka.classifiers.functions.neural.NeuralConnection
setY(int) - Method in class weka.gui.beans.BeanInstance
  Sets the y coordinate of this bean
setY(int) - Method in class weka.gui.visualize.AttributePanel
  shows which bar is the current y attribute.
setYAttribute(int) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel
  Set the y attribute index
setYAttribute(int) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
  Set the y axis fixed dimension
setYindex(int) - Method in class weka.gui.visualize.Plot2D
  Set the index of the attribute to go on the y axis
setYindex(int) - Method in class weka.gui.visualize.PlotData2D
  Set the y index of the data
setYIndex(int) - Method in class weka.gui.visualize.VisualizePanel
  Set the index of the attribute for the y axis
SFEntropyGain() - Method in class weka.classifiers.Evaluation
  Returns the total SF, which is the null model entropy minus the scheme entropy.
SFMeanEntropyGain() - Method in class weka.classifiers.Evaluation
  Returns the SF per instance, which is the null model entropy minus the scheme entropy, per instance.
SFMeanPriorEntropy() - Method in class weka.classifiers.Evaluation
  Returns the entropy per instance for the null model
SFMeanSchemeEntropy() - Method in class weka.classifiers.Evaluation
  Returns the entropy per instance for the scheme
SFPriorEntropy() - Method in class weka.classifiers.Evaluation
  Returns the total entropy for the null model
SFSchemeEntropy() - Method in class weka.classifiers.Evaluation
  Returns the total entropy for the scheme
shear(double, double) - Method in class weka.gui.visualize.PostscriptGraphics
shift(int, int) - Method in class weka.classifiers.functions.pace.IntVector
  Shifts an element to another position.
shift(int, int, Instance) - Method in class weka.classifiers.trees.j48.Distribution
  Shifts given instance from one bag to another one.
shiftBeans(BeanInstance, boolean) - Method in class weka.gui.beans.MetaBean
  Move coords of all inputs and outputs of this meta bean to the coords of the supplied BeanInstance.
shiftRange(int, int, Instances, int, int) - Method in class weka.classifiers.trees.j48.Distribution
  Shifts all instances in given range from one bag to another one.
shiftToEnd(int) - Method in class weka.classifiers.functions.pace.IntVector
  Shifts an element to the end of the vector.
SHORT - Static variable in class weka.core.converters.DatabaseLoader
SHORT - Static variable in class weka.experiment.DatabaseUtils
  Type mapping for SHORT used for reading experiment results
show(Component, int, int) - Method in class weka.gui.GenericObjectEditor.JTreePopupMenu
  Displays the menu, making sure it will fit on the screen.
showAttributes() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  displays all the attributes, returns the selected item or NULL if canceled
showChart() - Method in class weka.gui.beans.StripChart
  Popup the chart panel
showDialog() - Method in class weka.gui.experiment.OutputFormatDialog
  Pops up the modal dialog and waits for cancel or a selection.
showDialog() - Method in class weka.gui.ListSelectorDialog
  Pops up the modal dialog and waits for cancel or a selection.
showDialog() - Method in class weka.gui.PropertySelectorDialog
  Pops up the modal dialog and waits for cancel or a selection.
showDialog() - Method in class weka.gui.ViewerDialog
  Pops up the modal dialog and waits for Cancel or OK.
showDialog(Instances) - Method in class weka.gui.ViewerDialog
  Pops up the modal dialog and waits for Cancel or OK.
showInputBox(Component, String, String, Object) - Static method in class weka.gui.ComponentHelper
  pops up an input dialog
showMessageBox(Component, String, String, int, int) - Static method in class weka.gui.ComponentHelper
  displays a message box with the given title, message, buttons and icon ant the dimension.
showOutOfMemory() - Method in class weka.core.Memory
  prints an error message if OutOfMemory (and if GUI is present a dialog), otherwise nothing happens.
showProperties() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  displays some properties of the instances
showPropertyDialog() - Method in class weka.gui.PropertyPanel
  Displays the property edit dialog for the panel.
showResults() - Method in class weka.gui.beans.GraphViewer
  Popup a result list from which the user can select a graph to view
showResults() - Method in class weka.gui.beans.TextViewer
  Popup a component to display the selected text
showSaveDialog(Component) - Method in class weka.gui.arffviewer.FileChooser
  Pops up a "Save File" file chooser dialog
showTree() - Method in class weka.gui.HierarchyPropertyParser
  Show the whole tree in text format
showValues() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  displays all the distinct values for an attribute
shrinkageTipText() - Method in class weka.classifiers.meta.AdditiveRegression
  Returns the tip text for this property
shrinkageTipText() - Method in class weka.classifiers.meta.LogitBoost
  Returns the tip text for this property
shuffleTipText() - Method in class weka.classifiers.rules.Ridor
  Returns the tip text for this property
shuttlesort(int[], int[], int, int) - Method in class weka.gui.TableSorter
sigLevel - Variable in class weka.experiment.PairedStats
  The significance level for comparisons
sigmaTipText() - Method in class weka.attributeSelection.ReliefFAttributeEval
  Returns the tip text for this property
SigmoidUnit - Class in weka.classifiers.functions.neural
  This can be used by the neuralnode to perform all it's computations (as a sigmoid unit).
SigmoidUnit() - Constructor for class weka.classifiers.functions.neural.SigmoidUnit
sign() - Method in class weka.classifiers.functions.pace.DoubleVector
  Returns the signs of all elements in terms of -1, 0 and +1.
significanceLevelTipText() - Method in class weka.associations.Apriori
  Returns the tip text for this property
significanceLevelTipText() - Method in class weka.attributeSelection.RaceSearch
  Returns the tip text for this property
SIGNIFICANT - Static variable in class weka.associations.Tertius
SimpleCLI - Class in weka.gui
  Creates a very simple command line for invoking the main method of classes.
SimpleCLI() - Constructor for class weka.gui.SimpleCLI
  Constructor
SimpleDateFormatEditor - Class in weka.gui
  Class for editing SimpleDateFormat strings.
SimpleDateFormatEditor() - Constructor for class weka.gui.SimpleDateFormatEditor
  Constructs a new SimpleDateFormatEditor.
SimpleEstimator - Class in weka.classifiers.bayes.net.estimate
  SimpleEstimator is used for estimating the conditional probability tables of a Bayes network once the structure has been learned.
SimpleEstimator() - Constructor for class weka.classifiers.bayes.net.estimate.SimpleEstimator
SimpleKMeans - Class in weka.clusterers
  Simple k means clustering class.
SimpleKMeans() - Constructor for class weka.clusterers.SimpleKMeans
SimpleLinearRegression - Class in weka.classifiers.functions
  Class for learning a simple linear regression model.
SimpleLinearRegression() - Constructor for class weka.classifiers.functions.SimpleLinearRegression
SimpleLinkedList - Class in weka.associations.tertius
SimpleLinkedList() - Constructor for class weka.associations.tertius.SimpleLinkedList
SimpleLinkedList.LinkedListInverseIterator - Class in weka.associations.tertius
SimpleLinkedList.LinkedListInverseIterator() - Constructor for class weka.associations.tertius.SimpleLinkedList.LinkedListInverseIterator
SimpleLinkedList.LinkedListIterator - Class in weka.associations.tertius
SimpleLinkedList.LinkedListIterator() - Constructor for class weka.associations.tertius.SimpleLinkedList.LinkedListIterator
SimpleLogistic - Class in weka.classifiers.functions
  Class for building a logistic regression model using LogitBoost.
SimpleLogistic() - Constructor for class weka.classifiers.functions.SimpleLogistic
  Constructor for creating SimpleLogistic object with standard options.
SimpleLogistic(int, boolean, boolean) - Constructor for class weka.classifiers.functions.SimpleLogistic
  Constructor for creating SimpleLogistic object.
SimpleSetupPanel - Class in weka.gui.experiment
  This panel controls the configuration of an experiment.
SimpleSetupPanel(Experiment) - Constructor for class weka.gui.experiment.SimpleSetupPanel
  Creates the setup panel with the supplied initial experiment.
SimpleSetupPanel() - Constructor for class weka.gui.experiment.SimpleSetupPanel
  Creates the setup panel with no initial experiment.
SimulatedAnnealing - Class in weka.classifiers.bayes.net.search.global
  SimulatedAnnealing uses simulated annealing for learning Bayesian network structures.
SimulatedAnnealing() - Constructor for class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
SimulatedAnnealing - Class in weka.classifiers.bayes.net.search.local
  SimulatedAnnealing uses simulated annealing for learning Bayesian network structures.
SimulatedAnnealing() - Constructor for class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
SINE - Static variable in class weka.datagenerators.BIRCHCluster
SingleClassifierEnhancer - Class in weka.classifiers
  Abstract utility class for handling settings common to meta classifiers that use a single base learner.
SingleClassifierEnhancer() - Constructor for class weka.classifiers.SingleClassifierEnhancer
singleConsequence(Instances, int, FastVector) - Static method in class weka.associations.RuleGeneration
  generates a consequence of length 1 for an association rule.
SingleIndex - Class in weka.core
  Class representing a single cardinal number.
SingleIndex() - Constructor for class weka.core.SingleIndex
  Default constructor.
SingleIndex(String) - Constructor for class weka.core.SingleIndex
  Constructor to set initial index.
singletons(Instances) - Static method in class weka.associations.AprioriItemSet
  Converts the header info of the given set of instances into a set of item sets (singletons).
singletons(Instances) - Static method in class weka.associations.ItemSet
  Converts the header info of the given set of instances into a set of item sets (singletons).
singletons(Instances, Instances) - Static method in class weka.associations.LabeledItemSet
  Converts the header info of the given set of instances into a set of item sets (singletons).
SINGULAR_DUMMY - Static variable in interface weka.gui.graphvisualizer.GraphConstants
  SINGULAR_DUMMY node - node with only one outgoing edge i.e.
SingularValueDecomposition - Class in weka.core.matrix
  Singular Value Decomposition.
SingularValueDecomposition(Matrix) - Constructor for class weka.core.matrix.SingularValueDecomposition
  Construct the singular value decomposition
size() - Method in class weka.associations.tertius.SimpleLinkedList
size() - Method in class weka.classifiers.CostMatrix
  Gets the size of the matrix.
size() - Method in class weka.classifiers.evaluation.ConfusionMatrix
  Gets the number of classes.
size() - Method in class weka.classifiers.functions.pace.DiscreteFunction
  Returns the size of the point set.
size() - Method in class weka.classifiers.functions.pace.DoubleVector
  Gets the size of the vector.
size() - Method in class weka.classifiers.functions.pace.IntVector
  Gets the size of the vector.
size() - Method in class weka.classifiers.lazy.kstar.KStarCache.CacheTable
  Returns the number of keys in this hashtable.
size() - Method in class weka.classifiers.rules.Rule
  The size of the rule.
size() - Method in class weka.core.FastVector
  Returns the vector's current size.
size() - Method in class weka.core.Queue
  Gets queue's size.
size() - Method in class weka.core.xml.MethodHandler
  returns the number of currently stored Methods
sm(double, double) - Static method in class weka.core.Utils
  Tests if a is smaller than b.
SMALL - Static variable in class weka.core.Utils
  The small deviation allowed in double comparisons
SMO - Class in weka.classifiers.functions
  Implements John C.
SMO() - Constructor for class weka.classifiers.functions.SMO
smoothingParameterTipText() - Method in class weka.classifiers.bayes.ComplementNaiveBayes
  Returns the tip text for this property
SMOreg - Class in weka.classifiers.functions
  Implements Alex J.Smola and Bernhard Scholkopf sequential minimal optimization algorithm for training a support vector regression using polynomial or RBF kernels.
SMOreg() - Constructor for class weka.classifiers.functions.SMOreg
smOrEq(double, double) - Static method in class weka.core.Utils
  Tests if a is smaller or equal to b.
SMOset - Class in weka.classifiers.functions.supportVector
  Stores a set of integer of a given size.
SMOset(int) - Constructor for class weka.classifiers.functions.supportVector.SMOset
  Creates a new set of the given size.
solve(Matrix) - Method in class weka.core.matrix.CholeskyDecomposition
  Solve A*X = B
solve(Matrix) - Method in class weka.core.matrix.LUDecomposition
  Solve A*X = B
solve(Matrix) - Method in class weka.core.matrix.Matrix
  Solve A*X = B
solve(Matrix) - Method in class weka.core.matrix.QRDecomposition
  Least squares solution of A*X = B
solve(double[]) - Method in class weka.core.Matrix
  Deprecated. Solve A*X = B using backward substitution.
solveTranspose(Matrix) - Method in class weka.core.matrix.Matrix
  Solve X*A = B, which is also A'*X' = B'
solveTriangle(Matrix, double[], boolean, boolean[]) - Static method in class weka.core.Optimization
  Solve the linear equation of TX=B where T is a triangle matrix It can be solved using back/forward substitution, with O(N^2) complexity
sort(Comparator) - Method in class weka.associations.tertius.SimpleLinkedList
sort() - Method in class weka.classifiers.functions.pace.DiscreteFunction
  Sorts the point values of the discrete function.
sort() - Method in class weka.classifiers.functions.pace.DoubleVector
  Sorts the array in place
sort() - Method in class weka.classifiers.functions.pace.IntVector
  Sorts the elements in place
sort(int) - Method in class weka.core.Instances
  Sorts the instances based on an attribute.
sort(Attribute) - Method in class weka.core.Instances
  Sorts the instances based on an attribute.
sort(int[]) - Static method in class weka.core.Utils
  Sorts a given array of integers in ascending order and returns an array of integers with the positions of the elements of the original array in the sorted array.
sort(double[]) - Static method in class weka.core.Utils
  Sorts a given array of doubles in ascending order and returns an array of integers with the positions of the elements of the original array in the sorted array.
sort(Object) - Method in class weka.gui.TableSorter
sortByColumn(int) - Method in class weka.gui.TableSorter
sortByColumn(int, boolean) - Method in class weka.gui.TableSorter
sortClassesByRoot(String) - Static method in class weka.gui.GenericObjectEditor
  parses the given string of classes separated by ", " and returns the a hashtable with as many entries as there are different root elements in the class names (the key is the root element).
sortInstances() - Method in class weka.gui.arffviewer.ArffPanel
  sorts the instances via the currently selected column
sortInstances(int) - Method in class weka.gui.arffviewer.ArffTableModel
  sorts the instances via the given attribute
sortInstances(int) - Method in class weka.gui.arffviewer.ArffTableSorter
  sorts the instances via the given attribute
sortInstances() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  sorts the current selected attribute
sortWithIndex() - Method in class weka.classifiers.functions.pace.DoubleVector
  Sorts the array in place with index returned
sortWithIndex(int, int, IntVector) - Method in class weka.classifiers.functions.pace.DoubleVector
  Sorts the array in place with index changed
Sourcable - Interface in weka.classifiers
  Interface for classifiers that can be converted to Java source.
sourceClass(int, Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
sourceExpression(int, Instances) - Method in class weka.classifiers.trees.j48.BinC45Split
  Returns a string containing java source code equivalent to the test made at this node.
sourceExpression(int, Instances) - Method in class weka.classifiers.trees.j48.C45Split
  Returns a string containing java source code equivalent to the test made at this node.
sourceExpression(int, Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
sourceExpression(int, Instances) - Method in class weka.classifiers.trees.j48.NBTreeNoSplit
  Returns a string containing java source code equivalent to the test made at this node.
sourceExpression(int, Instances) - Method in class weka.classifiers.trees.j48.NBTreeSplit
  Returns a string containing java source code equivalent to the test made at this node.
sourceExpression(int, Instances) - Method in class weka.classifiers.trees.j48.NoSplit
  Returns a string containing java source code equivalent to the test made at this node.
sourceExpression(int, Instances) - Method in class weka.classifiers.trees.lmt.ResidualSplit
  Method not in use
SOUTH_CONNECTOR - Static variable in class weka.gui.beans.BeanVisual
SPARSE1 - Static variable in class weka.filters.unsupervised.attribute.RandomProjection
  The types of distributions that can be used for calculating the random matrix
SPARSE2 - Static variable in class weka.filters.unsupervised.attribute.RandomProjection
  The types of distributions that can be used for calculating the random matrix
sparseDataTipText() - Method in class weka.experiment.InstanceQuery
  Returns the tip text for this property
sparseIndices() - Method in class weka.classifiers.functions.SMO
  Returns the indices in sparse format.
SparseInstance - Class in weka.core
  Class for storing an instance as a sparse vector.
SparseInstance(Instance) - Constructor for class weka.core.SparseInstance
  Constructor that generates a sparse instance from the given instance.
SparseInstance(SparseInstance) - Constructor for class weka.core.SparseInstance
  Constructor that copies the info from the given instance.
SparseInstance(double, double[]) - Constructor for class weka.core.SparseInstance
  Constructor that generates a sparse instance from the given parameters.
SparseInstance(double, double[], int[], int) - Constructor for class weka.core.SparseInstance
  Constructor that inititalizes instance variable with given values.
SparseInstance(int) - Constructor for class weka.core.SparseInstance
  Constructor of an instance that sets weight to one, all values to be missing, and the reference to the dataset to null.
SparseToNonSparse - Class in weka.filters.unsupervised.instance
  A filter that converts all incoming sparse instances into non-sparse format.
SparseToNonSparse() - Constructor for class weka.filters.unsupervised.instance.SparseToNonSparse
sparseWeights() - Method in class weka.classifiers.functions.SMO
  Returns the weights in sparse format.
SpecialFunctions - Class in weka.core
  Class implementing some mathematical functions.
SpecialFunctions() - Constructor for class weka.core.SpecialFunctions
sphere - Variable in class weka.classifiers.lazy.kstar.KStarWrapper
  used/reused to hold the sphere size
splash(Image) - Static method in class weka.gui.SplashWindow
  Open's a splash window using the specified image.
splash(URL) - Static method in class weka.gui.SplashWindow
  Open's a splash window using the specified image.
SplashWindow - Class in weka.gui
  A Splash window.
split(Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
  Splits the given set of instances into subsets.
split() - Method in class weka.classifiers.trees.m5.RuleNode
  Finds an attribute and split point for this node
splitAtt() - Method in class weka.classifiers.trees.m5.RuleNode
  Get the index of the splitting attribute for this node
splitAttr() - Method in class weka.classifiers.trees.m5.CorrelationSplitInfo
  Returns the attribute used in this split
splitAttr() - Method in interface weka.classifiers.trees.m5.SplitEvaluate
  Returns the attribute used in this split
splitAttr() - Method in class weka.classifiers.trees.m5.YongSplitInfo
  Returns the attribute used in this split
SplitCriterion - Class in weka.classifiers.trees.j48
  Abstract class for computing splitting criteria with respect to distributions of class values.
SplitCriterion() - Constructor for class weka.classifiers.trees.j48.SplitCriterion
splitCritValue(Distribution) - Method in class weka.classifiers.trees.j48.EntropySplitCrit
  Computes entropy for given distribution.
splitCritValue(Distribution, Distribution) - Method in class weka.classifiers.trees.j48.EntropySplitCrit
  Computes entropy of test distribution with respect to training distribution.
splitCritValue(Distribution) - Method in class weka.classifiers.trees.j48.GainRatioSplitCrit
  This method is a straightforward implementation of the gain ratio criterion for the given distribution.
splitCritValue(Distribution, double, double) - Method in class weka.classifiers.trees.j48.GainRatioSplitCrit
  This method computes the gain ratio in the same way C4.5 does.
splitCritValue(Distribution) - Method in class weka.classifiers.trees.j48.InfoGainSplitCrit
  This method is a straightforward implementation of the information gain criterion for the given distribution.
splitCritValue(Distribution, double) - Method in class weka.classifiers.trees.j48.InfoGainSplitCrit
  This method computes the information gain in the same way C4.5 does.
splitCritValue(Distribution, double, double) - Method in class weka.classifiers.trees.j48.InfoGainSplitCrit
  This method computes the information gain in the same way C4.5 does.
splitCritValue(Distribution) - Method in class weka.classifiers.trees.j48.SplitCriterion
  Computes result of splitting criterion for given distribution.
splitCritValue(Distribution, Distribution) - Method in class weka.classifiers.trees.j48.SplitCriterion
  Computes result of splitting criterion for given training and test distributions.
splitCritValue(Distribution, Distribution, int) - Method in class weka.classifiers.trees.j48.SplitCriterion
  Computes result of splitting criterion for given training and test distributions and given number of classes.
splitCritValue(Distribution, Distribution, Distribution) - Method in class weka.classifiers.trees.j48.SplitCriterion
  Computes result of splitting criterion for given training and test distributions and given default distribution.
splitEnt(Distribution) - Method in class weka.classifiers.trees.j48.EntropyBasedSplitCrit
  Computes entropy after splitting without considering the class values.
SplitEvaluate - Interface in weka.classifiers.trees.m5
  Interface for objects that determine a split point on an attribute
SplitEvaluator - Interface in weka.experiment
  Interface to objects able to generate a fixed set of results for a particular split of a dataset.
splitEvaluatorTipText() - Method in class weka.experiment.CrossValidationResultProducer
  Returns the tip text for this property
splitEvaluatorTipText() - Method in class weka.experiment.RandomSplitResultProducer
  Returns the tip text for this property
splitItemSet(int, int[]) - Method in class weka.associations.PriorEstimation
  splits an item set into premise and consequence and constructs therefore an association rule.
splitOnResidualsTipText() - Method in class weka.classifiers.trees.LMT
  Returns the tip text for this property
splitOptions(String) - Static method in class weka.core.Utils
  Split up a string containing options into an array of strings, one for each option.
splitPointTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithValues
  Returns the tip text for this property
Splitter - Class in weka.classifiers.trees.adtree
  Abstract class representing a splitter node in an alternating tree.
Splitter() - Constructor for class weka.classifiers.trees.adtree.Splitter
splitVal() - Method in class weka.classifiers.trees.m5.RuleNode
  Get the split point for this node
splitValue() - Method in class weka.classifiers.trees.m5.CorrelationSplitInfo
  Returns the split value
splitValue() - Method in interface weka.classifiers.trees.m5.SplitEvaluate
  Returns the split value
splitValue() - Method in class weka.classifiers.trees.m5.YongSplitInfo
  Returns the split value
SpreadSubsample - Class in weka.filters.supervised.instance
  Produces a random subsample of a dataset.
SpreadSubsample() - Constructor for class weka.filters.supervised.instance.SpreadSubsample
sqrt() - Method in class weka.classifiers.functions.pace.DoubleVector
  Returns the square-root of all the elements in the vector
sqrt() - Method in class weka.core.matrix.Matrix
  returns the square root of the matrix, i.e., X from the equation X*X = A.
  Steps in the Calculation (see `sqrtm` in Matlab):
  perform eigenvalue decomposition
  [V,D]=eig(A) take the square root of all elements in D (only the ones with positive sign are considered for further computation)
  S=sqrt(D) calculate the root
  X=V*S/V, which can be also written as X=(V'\(V*S)')'

  Note: since this method uses other high-level methods, it generates several instances of matrices.
square() - Method in class weka.classifiers.functions.pace.DoubleVector
  Returns the squared vector
square(double) - Static method in class weka.classifiers.functions.pace.Maths
  Returns the square of a value
stableSort(double[]) - Static method in class weka.core.Utils
  Sorts a given array of doubles in ascending order and returns an array of integers with the positions of the elements of the original array in the sorted array.
Stacking - Class in weka.classifiers.meta
  Implements stacking.
Stacking() - Constructor for class weka.classifiers.meta.Stacking
StackingC - Class in weka.classifiers.meta
  Implements StackingC (more efficient version of stacking).
StackingC() - Constructor for class weka.classifiers.meta.StackingC
  The constructor.
Standardize - Class in weka.filters.unsupervised.attribute
  Standardizes all numeric attributes in the given dataset to have zero mean and unit variance.
Standardize() - Constructor for class weka.filters.unsupervised.attribute.Standardize
start() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel
  Start the plotting thread
start() - Method in class weka.gui.boundaryvisualizer.BoundaryPanelDistributed
  Start processing
startApp() - Static method in class weka.gui.beans.KnowledgeFlow
  Static method that can be called from a running program to launch the KnowledgeFlow
startLoading() - Method in class weka.gui.beans.Loader
  Start loading data
StartSetHandler - Interface in weka.attributeSelection
  Interface for search methods capable of doing something sensible given a starting set of attributes.
startSetTipText() - Method in class weka.attributeSelection.BestFirst
  Returns the tip text for this property
startSetTipText() - Method in class weka.attributeSelection.GeneticSearch
  Returns the tip text for this property
startSetTipText() - Method in class weka.attributeSelection.GreedyStepwise
  Returns the tip text for this property
startSetTipText() - Method in class weka.attributeSelection.RandomSearch
  Returns the tip text for this property
startSetTipText() - Method in class weka.attributeSelection.Ranker
  Returns the tip text for this property
startUpComplete() - Method in interface weka.gui.beans.StartUpListener
StartUpListener - Interface in weka.gui.beans
  Interface to something that can be notified of a successful startup
stateChanged(ChangeEvent) - Method in class weka.gui.arffviewer.ArffPanel
  Invoked when the target of the listener has changed its state.
stateChanged(ChangeEvent) - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  Invoked when the target of the listener has changed its state.
stateChanged(ChangeEvent) - Method in class weka.gui.ViewerDialog
  Invoked when the target of the listener has changed its state.
Statistics - Class in weka.core
  Class implementing some distributions, tests, etc.
Statistics() - Constructor for class weka.core.Statistics
Stats - Class in weka.classifiers.trees.j48
  Class implementing a statistical routine needed by J48 to compute its error estimate.
Stats() - Constructor for class weka.classifiers.trees.j48.Stats
Stats - Class in weka.experiment
  A class to store simple statistics
Stats() - Constructor for class weka.experiment.Stats
statusMessage(String) - Method in interface weka.gui.Logger
  Sends the supplied message to the status line.
statusMessage(String) - Method in class weka.gui.LogPanel
  Sends the supplied message to the status line.
statusMessage(String) - Method in class weka.gui.SysErrLog
  Sends the supplied message to the status line.
stdDev - Variable in class weka.experiment.Stats
  The std deviation of values at the last calculateDerived() call
STEP_FIELD_NAME - Static variable in class weka.experiment.LearningRateResultProducer
steplsqr(PaceMatrix, IntVector, int, int, boolean) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Stepwise least squares QR-decomposition of the problem A x = b
stepSizeTipText() - Method in class weka.experiment.LearningRateResultProducer
  Returns the tip text for this property
stop() - Method in class weka.gui.beans.AbstractDataSink
  Stop any processing that the bean might be doing.
stop() - Method in class weka.gui.beans.AbstractEvaluator
  Stop any processing that the bean might be doing.
stop() - Method in class weka.gui.beans.AbstractTestSetProducer
  Stop any processing that the bean might be doing.
stop() - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer
  Stop any processing that the bean might be doing.
stop() - Method in class weka.gui.beans.AbstractTrainingSetProducer
  Stop any processing that the bean might be doing.
stop() - Method in interface weka.gui.beans.BeanCommon
  Stop any processing that the bean might be doing.
stop() - Method in class weka.gui.beans.ClassAssigner
stop() - Method in class weka.gui.beans.Classifier
  Stop any classifier action
stop() - Method in class weka.gui.beans.ClassifierPerformanceEvaluator
  Try and stop any action
stop() - Method in class weka.gui.beans.ClassValuePicker
stop() - Method in class weka.gui.beans.Clusterer
  Stop any clusterer action
stop() - Method in class weka.gui.beans.ClustererPerformanceEvaluator
  Try and stop any action
stop() - Method in class weka.gui.beans.CrossValidationFoldMaker
  Stop any action
stop() - Method in class weka.gui.beans.Filter
  Stop all action if possible
stop() - Method in class weka.gui.beans.IncrementalClassifierEvaluator
  Stop all action
stop() - Method in class weka.gui.beans.MetaBean
  Stop all encapsulated beans
stop() - Method in class weka.gui.beans.PredictionAppender
stop() - Method in class weka.gui.beans.Saver
  Stops the bean
stop() - Method in class weka.gui.beans.StripChart
  Stop any processing that the bean might be doing.
stop() - Method in class weka.gui.beans.TestSetMaker
stop() - Method in class weka.gui.beans.TrainingSetMaker
  Stop any action
stop() - Method in class weka.gui.beans.TrainTestSplitMaker
  Stop processing
stopPlotting() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel
  Stop the plotting thread
stopThreads() - Method in class weka.core.Memory
  stops all the current threads, to make a restart possible
Stopwords - Class in weka.core
  Class that can test whether a given string is a stop word.
Stopwords() - Constructor for class weka.core.Stopwords
store(double, double, double) - Method in class weka.classifiers.lazy.kstar.KStarCache
  Stores the specified values in the cahce table for easy retrieval.
StratifiedRemoveFolds - Class in weka.filters.supervised.instance
  This filter takes a dataset and outputs folds suitable for cross validation.
StratifiedRemoveFolds() - Constructor for class weka.filters.supervised.instance.StratifiedRemoveFolds
stratify(Instances, int, Random) - Static method in class weka.classifiers.rules.RuleStats
  Stratify the given data into the given number of bags based on the class values.
stratify(int) - Method in class weka.core.Instances
  Stratifies a set of instances according to its class values if the class attribute is nominal (so that afterwards a stratified cross-validation can be performed).
StreamableFilter - Interface in weka.filters
  Interface for filters can work with a stream of instances.
STRING - Static variable in class weka.core.Attribute
  Constant set for attributes with string values.
STRING - Static variable in class weka.core.converters.DatabaseLoader
STRING - Static variable in class weka.experiment.DatabaseUtils
  Type mapping for STRING used for reading experiment results
stringFreeStructure() - Method in class weka.core.Instances
  Create a copy of the structure, but "cleanse" string types (i.e.
stringSize(FontMetrics) - Method in class weka.gui.treevisualizer.Edge
  This will calculate how large a rectangle using the FontMetrics passed that the lines of the label will take up
stringSize(FontMetrics) - Method in class weka.gui.treevisualizer.Node
  This will return the width and height of the rectangle that the text will fit into.
StringToNominal - Class in weka.filters.unsupervised.attribute
  Converts a string attribute (i.e.
StringToNominal() - Constructor for class weka.filters.unsupervised.attribute.StringToNominal
StringToWordVector - Class in weka.filters.unsupervised.attribute
  Converts String attributes into a set of attributes representing word occurrence information from the text contained in the strings.
StringToWordVector() - Constructor for class weka.filters.unsupervised.attribute.StringToWordVector
  Default constructor.
StringToWordVector(int) - Constructor for class weka.filters.unsupervised.attribute.StringToWordVector
  Constructor that allows specification of the target number of words in the output.
stringValue(int) - Method in class weka.core.Instance
  Returns the string value of a nominal, string, or date attribute for the instance.
stringValue(Attribute) - Method in class weka.core.Instance
  Returns the string value of a nominal, string, or date attribute for the instance.
StripChart - Class in weka.gui.beans
  Bean that can display a horizontally scrolling strip chart.
StripChart() - Constructor for class weka.gui.beans.StripChart
StripChartBeanInfo - Class in weka.gui.beans
  Bean info class for the strip chart bean
StripChartBeanInfo() - Constructor for class weka.gui.beans.StripChartBeanInfo
StripChartCustomizer - Class in weka.gui.beans
  GUI Customizer for the strip chart bean
StripChartCustomizer() - Constructor for class weka.gui.beans.StripChartCustomizer
sub(int, Instance) - Method in class weka.classifiers.trees.j48.Distribution
  Subtracts given instance from given bag.
subsetDL(double, double, double) - Static method in class weka.classifiers.rules.RuleStats
  Subset description length:
  S(t,k,p) = -k*log2(p)-(n-k)log2(1-p) Details see Quilan: "MDL and categorical theories (Continued)",ML95
subsetEstimate(DoubleVector) - Method in class weka.classifiers.functions.pace.NormalMixture
  Returns the estimate of optimal subset selection.
SubsetEvaluator - Class in weka.attributeSelection
  Abstract attribute subset evaluator.
SubsetEvaluator() - Constructor for class weka.attributeSelection.SubsetEvaluator
subsumes(Rule) - Method in class weka.associations.tertius.Rule
  Test if this rule subsumes another rule.
subsumptionTipText() - Method in class weka.associations.Tertius
  Returns the tip text for this property.
subtract(AprioriItemSet) - Method in class weka.associations.AprioriItemSet
  Subtracts an item set from another one.
subtract(Distribution) - Method in class weka.classifiers.trees.j48.Distribution
  Subtracts the given distribution from this one.
subtract(double, double) - Method in class weka.experiment.PairedStats
  Removes an observed pair of values.
subtract(double) - Method in class weka.experiment.Stats
  Removes a value to the observed values (no checking is done that the value being removed was actually added).
subtract(double, double) - Method in class weka.experiment.Stats
  Subtracts a value that has been seen n times from the observed values
subtreeRaisingTipText() - Method in class weka.classifiers.trees.J48
  Returns the tip text for this property
subvector(int, int) - Method in class weka.classifiers.functions.pace.DoubleVector
  Returns a subvector.
subvector(IntVector) - Method in class weka.classifiers.functions.pace.DoubleVector
  Returns a subvector.
subvector(int, int) - Method in class weka.classifiers.functions.pace.IntVector
  Returns a subvector.
subvector(IntVector) - Method in class weka.classifiers.functions.pace.IntVector
  Returns a subvector as indexed by an IntVector.
sum() - Method in class weka.classifiers.functions.pace.DoubleVector
  Returns the sum of all elements in the vector.
sum(double[]) - Static method in class weka.core.Utils
  Computes the sum of the elements of an array of doubles.
sum(int[]) - Static method in class weka.core.Utils
  Computes the sum of the elements of an array of integers.
sum - Variable in class weka.experiment.Stats
  The sum of values seen
sum2() - Method in class weka.classifiers.functions.pace.DoubleVector
  Returns the squared sum of all elements in the vector.
sum2(DoubleVector) - Method in class weka.classifiers.functions.pace.DoubleVector
  Returns ||u-v||^2
sum2(int, int, int, boolean) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Squared sum of a column or row in a matrix
sum2(boolean) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Squared sum of columns or rows of a matrix
Summarizable - Interface in weka.core
  Interface to something that provides a short textual summary (as opposed to toString() which is usually a fairly complete description) of itself.
sumOfWeights() - Method in class weka.core.Instances
  Computes the sum of all the instances' weights.
sumSq - Variable in class weka.experiment.Stats
  The sum of values squared seen
SupervisedFilter - Interface in weka.filters
  Interface for filters that make use of a class attribute.
support() - Method in class weka.associations.ItemSet
  Outputs the support for an item set.
support() - Method in class weka.associations.LabeledItemSet
  Outputs the support for an item set.
supportPoints(DoubleVector, int) - Method in class weka.classifiers.functions.pace.ChisqMixture
  Contructs the set of support points for mixture estimation.
supportPoints(DoubleVector, int) - Method in class weka.classifiers.functions.pace.MixtureDistribution
  Contructs the set of support points for mixture estimation.
supportPoints(DoubleVector, int) - Method in class weka.classifiers.functions.pace.NormalMixture
  Contructs the set of support points for mixture estimation.
supportsCustomEditor() - Method in class weka.gui.CostMatrixEditor
  Indicates whether the cost matrix can be edited in a GUI, which it can.
supportsCustomEditor() - Method in class weka.gui.FileEditor
  Returns true because we do support a custom editor.
supportsCustomEditor() - Method in class weka.gui.GenericArrayEditor
  Returns true because we do support a custom editor.
supportsCustomEditor() - Method in class weka.gui.GenericObjectEditor
  Returns true because we do support a custom editor.
supportsCustomEditor() - Method in class weka.gui.SimpleDateFormatEditor
  Indicates whether the date format can be edited in a GUI, which it can.
svd() - Method in class weka.core.matrix.Matrix
  Singular Value Decomposition
SVMAttributeEval - Class in weka.attributeSelection
  Class for Evaluating attributes individually by using the SVM classifier.
SVMAttributeEval() - Constructor for class weka.attributeSelection.SVMAttributeEval
  Constructor
swap(int, int) - Method in class weka.classifiers.functions.pace.DoubleVector
  Swaps the values stored at i and j
swap(int, int) - Method in class weka.classifiers.functions.pace.IntVector
  Swaps the values stored at i and j
swap(int, int) - Method in class weka.core.FastVector
  Swaps two elements in the vector.
swap(int, int) - Method in class weka.core.Instances
  Swaps two instances in the set.
swap(int, int) - Method in class weka.gui.TableSorter
SwapValues - Class in weka.filters.unsupervised.attribute
  Swaps two values of a nominal attribute.
SwapValues() - Constructor for class weka.filters.unsupervised.attribute.SwapValues
switchToAdvanced(Experiment) - Method in class weka.gui.experiment.SetupModePanel
  Switches to the advanced setup mode.
switchToSimple(Experiment) - Method in class weka.gui.experiment.SetupModePanel
  Switches to the simple setup mode only if allowed to.
symmetricalUncertainty(double[][]) - Static method in class weka.core.ContingencyTables
  Calculates the symmetrical uncertainty for base 2.
SymmetricalUncertAttributeEval - Class in weka.attributeSelection
  Class for Evaluating attributes individually by measuring symmetrical uncertainty with respect to the class.
SymmetricalUncertAttributeEval() - Constructor for class weka.attributeSelection.SymmetricalUncertAttributeEval
  Constructor
Sync(BayesNet) - Method in class weka.classifiers.bayes.net.BIFReader
  synchronizes the node ordering of this Bayes network with those in the other network (if possible).
synopsis() - Method in class weka.core.Option
  Returns the option's synopsis.
SysErrLog - Class in weka.gui
  This Logger just sends messages to System.err.
SysErrLog() - Constructor for class weka.gui.SysErrLog
SystemInfo - Class in weka.core
  This class prints some information about the system setup, like Java version, JVM settings etc.
SystemInfo() - Constructor for class weka.core.SystemInfo
  initializes the object and reads the system information

## T

TAB_INSTANCES - Static variable in class weka.gui.arffviewer.ArffPanel
  the name of the tab for instances that were set directly
tableChanged(TableModelEvent) - Method in class weka.gui.arffviewer.ArffTable
  This fine grain notification tells listeners the exact range of cells, rows, or columns that changed.
tableChanged(TableModelEvent) - Method in class weka.gui.TableMap
tableChanged(TableModelEvent) - Method in class weka.gui.TableSorter
tableExists(String) - Method in class weka.experiment.DatabaseUtils
  Checks that a given table exists.
TableMap - Class in weka.gui
  In a chain of data manipulators some behaviour is common.
TableMap() - Constructor for class weka.gui.TableMap
tableNameTipText() - Method in class weka.core.converters.DatabaseSaver
  Returns the tip text fo this property
TableSorter - Class in weka.gui
  A sorter for TableModels.
TableSorter() - Constructor for class weka.gui.TableSorter
TableSorter(TableModel) - Constructor for class weka.gui.TableSorter
tabuListTipText() - Method in class weka.classifiers.bayes.net.search.global.TabuSearch
tabuListTipText() - Method in class weka.classifiers.bayes.net.search.local.TabuSearch
TabuSearch - Class in weka.classifiers.bayes.net.search.global
  TabuSearch implements tabu search for learning Bayesian network structures.
TabuSearch() - Constructor for class weka.classifiers.bayes.net.search.global.TabuSearch
TabuSearch - Class in weka.classifiers.bayes.net.search.local
  TabuSearch implements tabu search for learning Bayesian network structures.
TabuSearch() - Constructor for class weka.classifiers.bayes.net.search.local.TabuSearch
Tag - Class in weka.core
  A `Tag` simply associates a numeric ID with a String description.
Tag(int, String) - Constructor for class weka.core.Tag
  Creates a new `Tag` instance.
TAG_OBJECT - Static variable in class weka.core.xml.XMLSerialization
  the tag for an object
TAG_OPTION - Static variable in class weka.core.xml.XMLOptions
  tag for a single option
TAG_OPTIONS - Static variable in class weka.core.xml.XMLOptions
  tag for a list of options
TAGS_ATTRIBUTETYPE - Static variable in class weka.filters.unsupervised.attribute.RemoveType
  Tag allowing selection of attribute type to delete
TAGS_CV_TYPE - Static variable in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
TAGS_DSTRS_TYPE - Static variable in class weka.filters.unsupervised.attribute.RandomProjection
TAGS_ESTIMATOR - Static variable in class weka.classifiers.functions.PaceRegression
TAGS_EVAL - Static variable in class weka.classifiers.meta.ThresholdSelector
TAGS_FILTER - Static variable in class weka.classifiers.functions.SMO
TAGS_FILTER - Static variable in class weka.classifiers.functions.SMOreg
TAGS_MATRIX_SOURCE - Static variable in class weka.classifiers.meta.CostSensitiveClassifier
TAGS_MATRIX_SOURCE - Static variable in class weka.classifiers.meta.MetaCost
TAGS_METHOD - Static variable in class weka.classifiers.meta.MultiClassClassifier
TAGS_MISSING - Static variable in class weka.classifiers.lazy.KStar
  Define possible missing value handling methods
TAGS_OPTIMIZE - Static variable in class weka.classifiers.meta.ThresholdSelector
TAGS_PRUNETYPE - Static variable in class weka.classifiers.meta.RacedIncrementalLogitBoost
TAGS_RANGE - Static variable in class weka.classifiers.meta.ThresholdSelector
TAGS_SCORE_TYPE - Static variable in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
TAGS_SEARCHPATH - Static variable in class weka.classifiers.trees.ADTree
TAGS_SELECTION - Static variable in class weka.associations.Apriori
TAGS_SELECTION - Static variable in class weka.attributeSelection.BestFirst
TAGS_SELECTION - Static variable in class weka.attributeSelection.RaceSearch
TAGS_SELECTION - Static variable in class weka.classifiers.functions.LinearRegression
TAGS_WEIGHTING - Static variable in class weka.classifiers.lazy.IBk
TAN - Class in weka.classifiers.bayes.net.search.global
  Search for TAN = Tree Augmented Naive Bayes network structure using cross validation as scoring criterium.
TAN() - Constructor for class weka.classifiers.bayes.net.search.global.TAN
TAN - Class in weka.classifiers.bayes.net.search.local
  Search for TAN = Tree Augmented Naive Bayes network structure N.
TAN() - Constructor for class weka.classifiers.bayes.net.search.local.TAN
Task - Interface in weka.experiment
  Interface to something that can be remotely executed as a task.
taskFinished() - Method in class weka.gui.LogPanel
  Record a task ending
taskFinished() - Method in interface weka.gui.TaskLogger
  Tells the task logger that a task has completed
taskFinished() - Method in class weka.gui.WekaTaskMonitor
  Tells the panel that a task has completed
TaskLogger - Interface in weka.gui
  Interface for objects that display log and display information on running tasks.
taskStarted() - Method in class weka.gui.LogPanel
  Record the starting of a new task
taskStarted() - Method in interface weka.gui.TaskLogger
  Tells the task logger that a new task has been started
taskStarted() - Method in class weka.gui.WekaTaskMonitor
  Tells the panel that a new task has been started
TaskStatusInfo - Class in weka.experiment
  A class holding information for tasks being executed on RemoteEngines.
TaskStatusInfo() - Constructor for class weka.experiment.TaskStatusInfo
tauVal(double[][]) - Static method in class weka.core.ContingencyTables
  Computes Goodman and Kruskal's tau-value for a contingency table.
Tertius - Class in weka.associations
  Class implementing a Tertius-type algorithm.
Tertius() - Constructor for class weka.associations.Tertius
  Constructor that sets the options to the default values.
test(String[]) - Static method in class weka.core.Instances
  Method for testing this class.
Test - Class in weka.datagenerators
  Class to represent a test.
  The string representation of the test can be supplied in standard notation or for a subset of types of attributes in Prolog notation.
  Following examples for all possible tests that can be represented by this class, given in standard notation.
  Examples of tests for numeric attributes:
  B >= 2.333
  B < 4.56
  Examples of tests for nominal attributes with more then 2 values:
  A = rain
  A != rain
  Examples of tests for nominal attribute with exactly 2 values:
  A = false
  A = true
  The Prolog notation is only supplied for numeric attributes and for nominal attributes that have the values "true" and "false".
  Following examples for the Prolog notation provided.
  Examples of tests for numeric attributes:
  The same as for standard notation above.
  Examples of tests for nominal attributes with values "true"and "false":
  A
  not(A)
  (Other nominal attributes are not supported by the Prolog notation.)
testCV(int, int) - Method in class weka.core.Instances
  Creates the test set for one fold of a cross-validation on the dataset.
TestSetEvent - Class in weka.gui.beans
  Event encapsulating a test set
TestSetEvent(Object, Instances) - Constructor for class weka.gui.beans.TestSetEvent
TestSetListener - Interface in weka.gui.beans
  Interface to something that can accpet test set events
TestSetMaker - Class in weka.gui.beans
  Bean that accepts data sets and produces test sets
TestSetMaker() - Constructor for class weka.gui.beans.TestSetMaker
TestSetMakerBeanInfo - Class in weka.gui.beans
  Bean info class for the test set maker bean.
TestSetMakerBeanInfo() - Constructor for class weka.gui.beans.TestSetMakerBeanInfo
TestSetProducer - Interface in weka.gui.beans
  Interface to something that can produce test sets
TextEvent - Class in weka.gui.beans
  Event that encapsulates some textual information
TextEvent(Object, String, String) - Constructor for class weka.gui.beans.TextEvent
  Creates a new `TextEvent` instance.
TextListener - Interface in weka.gui.beans
  Interface to something that can process a TextEvent
TextViewer - Class in weka.gui.beans
  Bean that collects and displays pieces of text
TextViewer() - Constructor for class weka.gui.beans.TextViewer
TextViewerBeanInfo - Class in weka.gui.beans
  Bean info class for the text viewer
TextViewerBeanInfo() - Constructor for class weka.gui.beans.TextViewerBeanInfo
TFTransformTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Returns the tip text for this property
theoryDL(int) - Method in class weka.classifiers.rules.RuleStats
  The description length of the theory for a given rule.
THRESHOLD_NAME - Static variable in class weka.classifiers.evaluation.CostCurve
THRESHOLD_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve
ThresholdCurve - Class in weka.classifiers.evaluation
  Generates points illustrating prediction tradeoffs that can be obtained by varying the threshold value between classes.
ThresholdCurve() - Constructor for class weka.classifiers.evaluation.ThresholdCurve
ThresholdDataEvent - Class in weka.gui.beans
  Event encapsulating classifier performance data based on varying a threshold over the classifier's predicted probabilities
ThresholdDataEvent(Object, PlotData2D) - Constructor for class weka.gui.beans.ThresholdDataEvent
ThresholdDataListener - Interface in weka.gui.beans
  Interface to something that can accept ThresholdDataEvents
ThresholdSelector - Class in weka.classifiers.meta
  Class for selecting a threshold on a probability output by a distribution classifier.
ThresholdSelector() - Constructor for class weka.classifiers.meta.ThresholdSelector
  Constructor.
thresholdTipText() - Method in class weka.attributeSelection.GreedyStepwise
  Returns the tip text for this property
thresholdTipText() - Method in class weka.attributeSelection.RaceSearch
  Returns the tip text for this property
thresholdTipText() - Method in class weka.attributeSelection.Ranker
  Returns the tip text for this property
thresholdTipText() - Method in class weka.attributeSelection.WrapperSubsetEval
  Returns the tip text for this property
thresholdTipText() - Method in class weka.classifiers.functions.PaceRegression
  Returns the tip text for this property
thresholdTipText() - Method in class weka.classifiers.functions.Winnow
  Returns the tip text for this property
thresholdTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified
  Returns the tip text for this property
ThresholdVisualizePanel - Class in weka.gui.visualize
  This panel is a VisualizePanel, with the added ablility to display the area under the ROC curve if an ROC curve is chosen.
ThresholdVisualizePanel() - Constructor for class weka.gui.visualize.ThresholdVisualizePanel
times(double) - Method in class weka.classifiers.functions.pace.DoubleVector
  Multiplies a scalar
times(DoubleVector) - Method in class weka.classifiers.functions.pace.DoubleVector
  Multiplies another DoubleVector element by element
times(double) - Method in class weka.classifiers.functions.pace.Matrix
  Multiply a matrix by a scalar, C = s*A
times(Matrix) - Method in class weka.classifiers.functions.pace.Matrix
  Linear algebraic matrix multiplication, A * B
times(int, int, int, PaceMatrix, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Multiplication between a row (or part of a row) of the first matrix and a column (or part or a column) of the second matrix.
times(double) - Method in class weka.core.matrix.Matrix
  Multiply a matrix by a scalar, C = s*A
times(Matrix) - Method in class weka.core.matrix.Matrix
  Linear algebraic matrix multiplication, A * B
timesEquals(double) - Method in class weka.classifiers.functions.pace.DiscreteFunction
  All function values are multiplied by a double
timesEquals(double) - Method in class weka.classifiers.functions.pace.DoubleVector
  Multiply a vector by a scalar in place, u = s * u
timesEquals(DoubleVector) - Method in class weka.classifiers.functions.pace.DoubleVector
  Multiplies another DoubleVector element by element in place
timesEquals(double) - Method in class weka.classifiers.functions.pace.Matrix
  Multiply a matrix by a scalar in place, A = s*A
timesEquals(double) - Method in class weka.core.matrix.Matrix
  Multiply a matrix by a scalar in place, A = s*A
TimeSeriesDelta - Class in weka.filters.unsupervised.attribute
  An instance filter that assumes instances form time-series data and replaces attribute values in the current instance with the difference between the current value and the equivalent attribute attribute value of some previous (or future) instance.
TimeSeriesDelta() - Constructor for class weka.filters.unsupervised.attribute.TimeSeriesDelta
TimeSeriesTranslate - Class in weka.filters.unsupervised.attribute
  An instance filter that assumes instances form time-series data and replaces attribute values in the current instance with the equivalent attribute values of some previous (or future) instance.
TimeSeriesTranslate() - Constructor for class weka.filters.unsupervised.attribute.TimeSeriesTranslate
TIMESTAMP_FIELD_NAME - Static variable in class weka.experiment.CrossValidationResultProducer
TIMESTAMP_FIELD_NAME - Static variable in class weka.experiment.RandomSplitResultProducer
TO_BE_RUN - Static variable in class weka.experiment.TaskStatusInfo
toArray() - Method in class weka.core.FastVector
  Returns all the elements of this vector as an array
toArray() - Method in class weka.core.xml.XMLOptions
  returns the current DOM document as string array (takes care of quotes!)
toClassDetailsString() - Method in class weka.classifiers.Evaluation
  Generates a breakdown of the accuracy for each class (with default title), incorporating various information-retrieval statistics, such as true/false positive rate, precision/recall/F-Measure.
toClassDetailsString(String) - Method in class weka.classifiers.Evaluation
  Generates a breakdown of the accuracy for each class, incorporating various information-retrieval statistics, such as true/false positive rate, precision/recall/F-Measure.
toCommandLine() - Method in class weka.core.xml.XMLOptions
  returns the given DOM document as command line
toCumulativeMarginDistributionString() - Method in class weka.classifiers.Evaluation
  Output the cumulative margin distribution as a string suitable for input for gnuplot or similar package.
toDoubleArray() - Method in class weka.core.BinarySparseInstance
  Returns the values of each attribute as an array of doubles.
toDoubleArray() - Method in class weka.core.Instance
  Returns the values of each attribute as an array of doubles.
toDoubleArray() - Method in class weka.core.SparseInstance
  Returns the values of each attribute as an array of doubles.
toGraph() - Method in class weka.classifiers.trees.RandomTree
  Outputs the decision tree as a graph
toGraph(StringBuffer, int) - Method in class weka.classifiers.trees.RandomTree
  Outputs one node for graph.
tokenize(String) - Method in class weka.gui.HierarchyPropertyParser
  Tokenize the given string based on the seperator and put the tokens into an array of strings
toleranceParameterTipText() - Method in class weka.attributeSelection.SVMAttributeEval
  Returns a tip text for this property suitable for display in the GUI
toleranceParameterTipText() - Method in class weka.classifiers.functions.SMO
  Returns the tip text for this property
toleranceParameterTipText() - Method in class weka.classifiers.functions.SMOreg
  Returns the tip text for this property
toMatlab() - Method in class weka.core.matrix.Matrix
  converts the Matrix into a single line Matlab string: matrix is enclosed by parentheses, rows are separated by semicolon and single cells by blanks, e.g., [1 2; 3 4].
toMatlab() - Method in class weka.core.Matrix
  Deprecated. converts the Matrix into a single line Matlab string: matrix is enclosed by parentheses, rows are separated by semicolon and single cells by blanks, e.g., [1 2; 3 4].
toMatrixString() - Method in class weka.classifiers.Evaluation
  Calls toMatrixString() with a default title.
toMatrixString(String) - Method in class weka.classifiers.Evaluation
  Outputs the performance statistics as a classification confusion matrix.
toOutput() - Method in class weka.gui.visualize.JComponentWriter
  saves the current component to the currently set file.
toOutput(JComponent, File) - Static method in class weka.gui.visualize.JPEGWriter
  outputs the given component as JPEG in the specified file
toOutput() - Method in class weka.gui.visualize.JPEGWriter
  saves the current component to the currently set file
toOutput(JComponent, File) - Static method in class weka.gui.visualize.PostscriptWriter
  outputs the given component as Postscript in the specified file
toOutput() - Method in class weka.gui.visualize.PostscriptWriter
  saves the current component to the currently set file
topOfTree() - Method in class weka.classifiers.trees.m5.Rule
  Returns the top of the tree.
toPrologString() - Method in class weka.datagenerators.Test
  Returns the test represented by a string in Prolog notation.
toResultsString() - Method in class weka.attributeSelection.AttributeSelection
  get a description of the attribute selection
toSource(String) - Method in class weka.classifiers.meta.AdaBoostM1
  Returns the boosted model as Java source code.
toSource(String) - Method in class weka.classifiers.meta.LogitBoost
  Returns the boosted model as Java source code.
toSource(String) - Method in interface weka.classifiers.Sourcable
  Returns a string that describes the classifier as source.
toSource(String) - Method in class weka.classifiers.trees.DecisionStump
  Returns the decision tree as Java source code.
toSource(String) - Method in class weka.classifiers.trees.j48.ClassifierTree
  Returns source code for the tree as an if-then statement.
toSource(String) - Method in class weka.classifiers.trees.J48
  Returns tree as an if-then statement.
toSource(String) - Method in class weka.classifiers.trees.REPTree
  Returns the tree as if-then statements.
toString() - Method in class weka.associations.Apriori
  Outputs the size of all the generated sets of itemsets and the rules.
toString(Instances) - Method in class weka.associations.AprioriItemSet
  Returns the contents of an item set as a string.
toString(Instances) - Method in class weka.associations.ItemSet
  Returns the contents of an item set as a string.
toString() - Method in class weka.associations.PredictiveApriori
  Outputs the association rules.
toString() - Method in class weka.associations.tertius.AttributeValueLiteral
toString() - Method in class weka.associations.tertius.Body
  Gives a String representation of this set of literals as a conjunction.
toString() - Method in class weka.associations.tertius.Head
  Gives a String representation of this set of literals as a disjunction.
toString() - Method in class weka.associations.tertius.Literal
toString() - Method in class weka.associations.tertius.LiteralSet
  Gives a String representation for this set of literals.
toString() - Method in class weka.associations.tertius.Predicate
toString() - Method in class weka.associations.tertius.Rule
  Retrun a String for this rule.
toString() - Method in class weka.associations.tertius.SimpleLinkedList
toString() - Method in class weka.associations.Tertius
  Outputs the best rules found with their confirmation value and number of counter-instances.
toString() - Method in class weka.attributeSelection.BestFirst.Link2
toString() - Method in class weka.attributeSelection.BestFirst
  returns a description of the search as a String
toString() - Method in class weka.attributeSelection.CfsSubsetEval
  returns a string describing CFS
toString() - Method in class weka.attributeSelection.ChiSquaredAttributeEval
  Describe the attribute evaluator
toString() - Method in class weka.attributeSelection.ClassifierSubsetEval
  Returns a string describing classifierSubsetEval
toString(Instances, int) - Method in class weka.attributeSelection.ConsistencySubsetEval.hashKey
  Convert a hash entry to a string
toString() - Method in class weka.attributeSelection.ConsistencySubsetEval
  returns a description of the evaluator
toString() - Method in class weka.attributeSelection.ExhaustiveSearch
  prints a description of the search
toString() - Method in class weka.attributeSelection.GainRatioAttributeEval
  Return a description of the evaluator
toString() - Method in class weka.attributeSelection.GeneticSearch
  returns a description of the search
toString() - Method in class weka.attributeSelection.GreedyStepwise
  returns a description of the search.
toString() - Method in class weka.attributeSelection.InfoGainAttributeEval
  Describe the attribute evaluator
toString() - Method in class weka.attributeSelection.OneRAttributeEval
  Return a description of the evaluator
toString() - Method in class weka.attributeSelection.PrincipalComponents
  Returns a description of this attribute transformer
toString() - Method in class weka.attributeSelection.RaceSearch
toString() - Method in class weka.attributeSelection.RandomSearch
  prints a description of the search
toString() - Method in class weka.attributeSelection.Ranker
  returns a description of the search as a String
toString() - Method in class weka.attributeSelection.RankSearch
  returns a description of the search as a String
toString() - Method in class weka.attributeSelection.ReliefFAttributeEval
  Return a description of the ReliefF attribute evaluator.
toString() - Method in class weka.attributeSelection.SVMAttributeEval
  Return a description of the evaluator
toString() - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval
  Return a description of the evaluator
toString() - Method in class weka.attributeSelection.WrapperSubsetEval
  Returns a string describing the wrapper
toString() - Method in class weka.classifiers.bayes.AODE
  Returns a description of the classifier.
toString() - Method in class weka.classifiers.bayes.BayesNet
  Returns a description of the classifier.
toString() - Method in class weka.classifiers.bayes.ComplementNaiveBayes
  Prints out the internal model built by the classifier.
toString() - Method in class weka.classifiers.bayes.NaiveBayes
  Returns a description of the classifier.
toString() - Method in class weka.classifiers.bayes.NaiveBayesMultinomial
toString() - Method in class weka.classifiers.bayes.NaiveBayesSimple
  Returns a description of the classifier.
toString() - Method in class weka.classifiers.bayes.net.BayesNetGenerator
toString() - Method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes
  Display a representation of this estimator
toString() - Method in class weka.classifiers.bayes.net.search.SearchAlgorithm
toString() - Method in class weka.classifiers.BVDecompose
  Returns description of the bias-variance decomposition results.
toString() - Method in class weka.classifiers.BVDecomposeSegCVSub
  Returns description of the bias-variance decomposition results.
toString() - Method in class weka.classifiers.evaluation.ConfusionMatrix
  Calls toString() with a default title.
toString(String) - Method in class weka.classifiers.evaluation.ConfusionMatrix
  Outputs the performance statistics as a classification confusion matrix.
toString() - Method in class weka.classifiers.evaluation.NominalPrediction
  Gets a human readable representation of this prediction.
toString() - Method in class weka.classifiers.evaluation.NumericPrediction
  Gets a human readable representation of this prediction.
toString() - Method in class weka.classifiers.evaluation.TwoClassStats
  Returns a string containing the various performance measures for the current object
toString() - Method in class weka.classifiers.functions.LeastMedSq
  Returns a string representing the best LinearRegression classifier found.
toString() - Method in class weka.classifiers.functions.LinearRegression
  Outputs the linear regression model as a string.
toString() - Method in class weka.classifiers.functions.Logistic
  Gets a string describing the classifier.
toString() - Method in class weka.classifiers.functions.MultilayerPerceptron
toString() - Method in class weka.classifiers.functions.pace.ChisqMixture
  Converts to a string
toString() - Method in class weka.classifiers.functions.pace.DiscreteFunction
  Converts the discrete function to string.
toString() - Method in class weka.classifiers.functions.pace.DoubleVector
  Convert the DoubleVecor to a string
toString(int, boolean) - Method in class weka.classifiers.functions.pace.DoubleVector
  Convert the DoubleVecor to a string
toString() - Method in class weka.classifiers.functions.pace.IntVector
  Converts the IntVecor to a string
toString(int, boolean) - Method in class weka.classifiers.functions.pace.IntVector
  Convert the IntVecor to a string
toString() - Method in class weka.classifiers.functions.pace.MixtureDistribution
  Converts to a string
toString() - Method in class weka.classifiers.functions.pace.NormalMixture
  Converts to a string
toString() - Method in class weka.classifiers.functions.pace.PaceMatrix
  Converts matrix to string
toString(int, boolean) - Method in class weka.classifiers.functions.pace.PaceMatrix
  Converts matrix to string
toString() - Method in class weka.classifiers.functions.PaceRegression
  Outputs the linear regression model as a string.
toString() - Method in class weka.classifiers.functions.RBFNetwork
  Returns a description of this classifier as a String
toString() - Method in class weka.classifiers.functions.SimpleLinearRegression
  Returns a description of this classifier as a string
toString() - Method in class weka.classifiers.functions.SimpleLogistic
  Returns a description of the logistic model (attributes/coefficients).
toString() - Method in class weka.classifiers.functions.SMO
  Prints out the classifier.
toString() - Method in class weka.classifiers.functions.SMOreg
  Prints out the classifier.
toString() - Method in class weka.classifiers.functions.VotedPerceptron
  Returns textual description of classifier.
toString() - Method in class weka.classifiers.functions.Winnow
  Returns textual description of the classifier.
toString() - Method in class weka.classifiers.lazy.IB1
  Returns a description of this classifier.
toString() - Method in class weka.classifiers.lazy.IBk
  Returns a description of this classifier.
toString() - Method in class weka.classifiers.lazy.KStar
  Returns a description of this classifier.
toString() - Method in class weka.classifiers.lazy.LBR
  Returns a description of the classifier.
toString() - Method in class weka.classifiers.lazy.LWL
  Returns a description of this classifier.
toString() - Method in class weka.classifiers.meta.AdaBoostM1
  Returns description of the boosted classifier.
toString() - Method in class weka.classifiers.meta.AdditiveRegression
  Returns textual description of the classifier.
toString() - Method in class weka.classifiers.meta.AttributeSelectedClassifier
  Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.Bagging
  Returns description of the bagged classifier.
toString() - Method in class weka.classifiers.meta.ClassificationViaRegression
  Prints the classifiers.
toString() - Method in class weka.classifiers.meta.CostSensitiveClassifier
  Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.CVParameterSelection
  Returns description of the cross-validated classifier.
toString() - Method in class weka.classifiers.meta.Decorate
  Returns description of the Decorate classifier.
toString() - Method in class weka.classifiers.meta.FilteredClassifier
  Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.Grading
  Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.LogitBoost
  Returns description of the boosted classifier.
toString() - Method in class weka.classifiers.meta.MetaCost
  Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.MultiBoostAB
  Returns description of the boosted classifier.
toString() - Method in class weka.classifiers.meta.MultiClassClassifier
  Prints the classifiers.
toString() - Method in class weka.classifiers.meta.MultiScheme
  Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.OrdinalClassClassifier
  Prints the classifiers.
toString() - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost
  Returns description of the boosted classifier.
toString() - Method in class weka.classifiers.meta.RandomCommittee
  Returns description of the committee.
toString() - Method in class weka.classifiers.meta.RegressionByDiscretization
  Returns a description of the classifier.
toString() - Method in class weka.classifiers.meta.Stacking
  Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.StackingC
  Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.ThresholdSelector
  Returns description of the cross-validated classifier.
toString() - Method in class weka.classifiers.meta.Vote
  Output a representation of this classifier
toString() - Method in class weka.classifiers.misc.HyperPipes
  Returns a description of this classifier.
toString() - Method in class weka.classifiers.misc.VFI
  Returns a description of this classifier.
toString(String, String) - Method in class weka.classifiers.rules.ConjunctiveRule
  Prints this rule with the specified class label
toString() - Method in class weka.classifiers.rules.ConjunctiveRule
  Prints this rule
toString(Instances, int) - Method in class weka.classifiers.rules.DecisionTable.hashKey
  Convert a hash entry to a string
toString() - Method in class weka.classifiers.rules.DecisionTable.Link
  Returns string representation.
toString() - Method in class weka.classifiers.rules.DecisionTable
  Returns a description of the classifier.
toString() - Method in class weka.classifiers.rules.JRip
  Prints the all the rules of the rule learner.
toString() - Method in class weka.classifiers.rules.NNge
  Returns a description of this classifier.
toString() - Method in class weka.classifiers.rules.OneR
  Returns a description of the classifier
toString() - Method in class weka.classifiers.rules.part.ClassifierDecList
  Prints rules.
toString() - Method in class weka.classifiers.rules.part.MakeDecList
  Outputs the classifier into a string.
toString() - Method in class weka.classifiers.rules.PART
  Returns a description of the classifier
toString() - Method in class weka.classifiers.rules.Prism
  Prints a description of the classifier.
toString() - Method in class weka.classifiers.rules.Ridor
  Prints the all the rules of the rule learner.
toString() - Method in class weka.classifiers.rules.ZeroR
  Returns a description of the classifier.
toString() - Method in class weka.classifiers.trees.ADTree
  Returns a description of the classifier.
toString() - Method in class weka.classifiers.trees.DecisionStump
  Returns a description of the classifier.
toString() - Method in class weka.classifiers.trees.Id3
  Prints the decision tree using the private toString method from below.
toString() - Method in class weka.classifiers.trees.j48.ClassifierTree
  Prints tree structure.
toString() - Method in class weka.classifiers.trees.j48.NBTreeClassifierTree
  Prints tree structure.
toString() - Method in class weka.classifiers.trees.j48.NBTreeNoSplit
  Return a textual description of the node
toString() - Method in class weka.classifiers.trees.J48
  Returns a description of the classifier.
toString() - Method in class weka.classifiers.trees.lmt.LMTNode
  Returns a description of the logistic model tree (tree structure and logistic models)
toString() - Method in class weka.classifiers.trees.lmt.LogisticBase
  Returns a description of the logistic model (i.e., attributes and coefficients).
toString() - Method in class weka.classifiers.trees.LMT
  Returns a description of the classifier.
toString() - Method in class weka.classifiers.trees.m5.Impurity
  Converts an Impurity object to a string
toString() - Method in class weka.classifiers.trees.m5.M5Base
  Returns a description of the classifier
toString() - Method in class weka.classifiers.trees.m5.PreConstructedLinearModel
  Returns a textual description of this linear model
toString() - Method in class weka.classifiers.trees.m5.Rule
  Return a description of the m5 tree or rule
toString() - Method in class weka.classifiers.trees.m5.RuleNode
  print the linear model at this node
toString() - Method in class weka.classifiers.trees.m5.Values
  Converts the stats to a string
toString(Instances) - Method in class weka.classifiers.trees.m5.YongSplitInfo
  Converts the spliting information to string
toString() - Method in class weka.classifiers.trees.NBTree
  Returns a description of the classifier.
toString() - Method in class weka.classifiers.trees.RandomForest
  Outputs a description of this classifier.
toString() - Method in class weka.classifiers.trees.RandomTree
  Outputs the decision tree.
toString() - Method in class weka.classifiers.trees.REPTree
  Outputs the decision tree.
toString() - Method in class weka.classifiers.trees.UserClassifier
toString() - Method in class weka.clusterers.Cobweb
  Returns a description of the clusterer as a string.
toString() - Method in class weka.clusterers.EM
  Outputs the generated clusters into a string.
toString() - Method in class weka.clusterers.FarthestFirst
  return a string describing this clusterer
toString() - Method in class weka.clusterers.MakeDensityBasedClusterer
  Returns a description of the clusterer.
toString() - Method in class weka.clusterers.SimpleKMeans
  return a string describing this clusterer
toString() - Method in class weka.core.Attribute
  Returns a description of this attribute in ARFF format.
toString() - Method in class weka.core.AttributeStats
  Returns a human readable representation of this AttributeStats instance.
toString() - Method in class weka.core.BinarySparseInstance
  Returns the description of one instance in sparse format.
toString() - Method in class weka.core.Instance
  Returns the description of one instance.
toString(int) - Method in class weka.core.Instance
  Returns the description of one value of the instance as a string.
toString(Attribute) - Method in class weka.core.Instance
  Returns the description of one value of the instance as a string.
toString() - Method in class weka.core.Instances
  Returns the dataset as a string in ARFF format.
toString() - Method in class weka.core.matrix.LinearRegression
  returns the coefficients in a string representation
toString() - Method in class weka.core.matrix.Matrix
  Converts a matrix to a string
toString() - Method in class weka.core.Matrix
  Deprecated. Converts a matrix to a string
toString() - Method in class weka.core.Queue
  Produces textual description of queue.
toString() - Method in class weka.core.Range
  Constructs a representation of the current range.
toString() - Method in class weka.core.SingleIndex
  Constructs a representation of the current range.
toString() - Method in class weka.core.SparseInstance
  Returns the description of one instance in sparse format.
toString() - Method in class weka.core.SystemInfo
  returns a string representation of all the system properties
toString() - Method in class weka.core.xml.MethodHandler
  returns the internal Hashtable (propety/class - method relationship) in a string representation
toString() - Method in class weka.core.xml.XMLDocument
  returns the current DOM document as XML-string
toString() - Method in class weka.core.xml.XMLOptions
  returns the object in a string representation (as indented XML output)
toString() - Method in class weka.core.xml.XMLSerializationMethodHandler
  returns the read and write method handlers as string
toString() - Method in class weka.datagenerators.Test
  Returns the test represented by a string.
toString() - Method in class weka.estimators.DDConditionalEstimator
  Display a representation of this estimator
toString() - Method in class weka.estimators.DiscreteEstimator
  Display a representation of this estimator
toString() - Method in class weka.estimators.DKConditionalEstimator
  Display a representation of this estimator
toString() - Method in class weka.estimators.DNConditionalEstimator
  Display a representation of this estimator
toString() - Method in class weka.estimators.KDConditionalEstimator
  Display a representation of this estimator
toString() - Method in class weka.estimators.KernelEstimator
  Display a representation of this estimator
toString() - Method in class weka.estimators.KKConditionalEstimator
  Display a representation of this estimator
toString() - Method in class weka.estimators.MahalanobisEstimator
  Display a representation of this estimator
toString() - Method in class weka.estimators.NDConditionalEstimator
  Display a representation of this estimator
toString() - Method in class weka.estimators.NNConditionalEstimator
  Display a representation of this estimator
toString() - Method in class weka.estimators.NormalEstimator
  Display a representation of this estimator
toString() - Method in class weka.estimators.PoissonEstimator
  Display a representation of this estimator
toString() - Method in class weka.experiment.AveragingResultProducer
  Gets a text descrption of the result producer.
toString() - Method in class weka.experiment.ClassifierSplitEvaluator
  Returns a text description of the split evaluator.
toString() - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator
  Returns a text description of the split evaluator.
toString() - Method in class weka.experiment.CrossValidationResultProducer
  Gets a text descrption of the result producer.
toString() - Method in class weka.experiment.DatabaseResultProducer
  Gets a text descrption of the result producer.
toString() - Method in class weka.experiment.Experiment
  Gets a string representation of the experiment configuration.
toString() - Method in class weka.experiment.LearningRateResultProducer
  Gets a text descrption of the result producer.
toString() - Method in class weka.experiment.PairedStats
  Returns statistics on the paired comparison.
toString() - Method in class weka.experiment.PropertyNode
  Returns a string description of this property.
toString() - Method in class weka.experiment.RandomSplitResultProducer
  Gets a text descrption of the result producer.
toString() - Method in class weka.experiment.RegressionSplitEvaluator
  Returns a text description of the split evaluator.
toString() - Method in class weka.experiment.RemoteExperiment
  Overides toString in Experiment
toString() - Method in class weka.experiment.Stats
  Returns a string summarising the stats so far.
toString() - Method in class weka.gui.arffviewer.ArffViewer
  returns only the classname
toString() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  returns only the classname
toString() - Method in class weka.gui.graphvisualizer.GraphEdge
toSummaryString() - Method in class weka.classifiers.Evaluation
  Calls toSummaryString() with no title and no complexity stats
toSummaryString(boolean) - Method in class weka.classifiers.Evaluation
  Calls toSummaryString() with a default title.
toSummaryString(String, boolean) - Method in class weka.classifiers.Evaluation
  Outputs the performance statistics in summary form.
toSummaryString() - Method in class weka.classifiers.meta.CVParameterSelection
toSummaryString() - Method in class weka.classifiers.rules.PART
  Returns a superconcise version of the model
toSummaryString() - Method in class weka.classifiers.trees.J48
  Returns a superconcise version of the model
toSummaryString() - Method in class weka.classifiers.trees.NBTree
  Returns a superconcise version of the model
toSummaryString() - Method in class weka.core.Instances
  Generates a string summarizing the set of instances.
toSummaryString() - Method in interface weka.core.Summarizable
  Returns a string that summarizes the object.
total() - Method in class weka.classifiers.evaluation.ConfusionMatrix
  Gets the number of predictions that were made (actually the sum of the weights of predictions where the class value was known).
total() - Method in class weka.classifiers.trees.j48.Distribution
  Returns total number of (possibly fractional) instances.
totalCost() - Method in class weka.classifiers.Evaluation
  Gets the total cost, that is, the cost of each prediction times the weight of the instance, summed over all instances.
totalCount - Variable in class weka.core.AttributeStats
  The total number of values (i.e.
toXML(Object) - Method in class weka.core.xml.XMLSerialization
  extracts all accesible properties from the given object
toXMLBIF03() - Method in class weka.classifiers.bayes.BayesNet
  Returns a description of the classifier in XML BIF 0.3 format.
TP_RATE_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve
trace() - Method in class weka.classifiers.functions.pace.Matrix
  Matrix trace.
trace() - Method in class weka.core.matrix.Matrix
  Matrix trace.
trainCV(int, int) - Method in class weka.core.Instances
  Creates the training set for one fold of a cross-validation on the dataset.
trainCV(int, int, Random) - Method in class weka.core.Instances
  Creates the training set for one fold of a cross-validation on the dataset.
TrainingSetEvent - Class in weka.gui.beans
  Event encapsulating a training set
TrainingSetEvent(Object, Instances) - Constructor for class weka.gui.beans.TrainingSetEvent
  Creates a new `TrainingSetEvent`
TrainingSetListener - Interface in weka.gui.beans
  Interface to something that can accept and process training set events
TrainingSetMaker - Class in weka.gui.beans
  Bean that accepts a data sets and produces a training set
TrainingSetMaker() - Constructor for class weka.gui.beans.TrainingSetMaker
TrainingSetMakerBeanInfo - Class in weka.gui.beans
  Bean info class for the training set maker bean
TrainingSetMakerBeanInfo() - Constructor for class weka.gui.beans.TrainingSetMakerBeanInfo
TrainingSetProducer - Interface in weka.gui.beans
  Interface to something that can produce a training set
trainingTimeTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
trainPercentTipText() - Method in class weka.experiment.RandomSplitResultProducer
  Returns the tip text for this property
trainPercentTipText() - Method in class weka.gui.beans.TrainTestSplitMaker
  Tip text info for this property
TrainTestSplitMaker - Class in weka.gui.beans
  Bean that accepts data sets, training sets, test sets and produces both a training and test set by randomly spliting the data
TrainTestSplitMaker() - Constructor for class weka.gui.beans.TrainTestSplitMaker
TrainTestSplitMakerBeanInfo - Class in weka.gui.beans
  Bean info class for the train test split maker bean
TrainTestSplitMakerBeanInfo() - Constructor for class weka.gui.beans.TrainTestSplitMakerBeanInfo
TrainTestSplitMakerCustomizer - Class in weka.gui.beans
  GUI customizer for the train test split maker bean
TrainTestSplitMakerCustomizer() - Constructor for class weka.gui.beans.TrainTestSplitMakerCustomizer
transform(AffineTransform) - Method in class weka.gui.visualize.PostscriptGraphics
transformAllValuesTipText() - Method in class weka.filters.supervised.attribute.NominalToBinary
  Returns the tip text for this property
transformBackToOriginalTipText() - Method in class weka.attributeSelection.PrincipalComponents
  Returns the tip text for this property
transformedData() - Method in interface weka.attributeSelection.AttributeTransformer
  Returns the transformed data
transformedData() - Method in class weka.attributeSelection.PrincipalComponents
  Gets the transformed training data.
transformedHeader() - Method in interface weka.attributeSelection.AttributeTransformer
  Returns just the header for the transformed data (ie.
transformedHeader() - Method in class weka.attributeSelection.PrincipalComponents
  Returns just the header for the transformed data (ie.
translate(int, int) - Method in class weka.gui.visualize.PostscriptGraphics
  Translates the origin of the graphics context to the point (x, y) in the current coordinate system.
translate(double, double) - Method in class weka.gui.visualize.PostscriptGraphics
translateDBColumnType(String) - Method in class weka.experiment.DatabaseUtils
  translates the column data type string to an integer value that indicates which data type / get()-Method to use in order to retrieve values from the database (see DatabaseUtils.Properties, InstanceQuery()).
transpose() - Method in class weka.classifiers.functions.pace.Matrix
  Matrix transpose.
transpose() - Method in class weka.core.matrix.Matrix
  Matrix transpose.
transpose() - Method in class weka.core.Matrix
  Deprecated. Returns the transpose of a matrix.
transProb() - Method in class weka.classifiers.lazy.kstar.KStarNominalAttribute
  Calculates the probability of the indexed nominal attribute of the test instance transforming into the indexed nominal attribute of the training instance.
transProb() - Method in class weka.classifiers.lazy.kstar.KStarNumericAttribute
  Calculates the transformation probability of the attribute indexed "m_AttrIndex" in test instance "m_Test" to the same attribute in the train instance "m_Train".
TREE - Static variable in interface weka.core.Drawable
TreeBuild - Class in weka.gui.treevisualizer
  This class will parse a dotty file and construct a tree structure from it with Edge's and Node's
TreeBuild() - Constructor for class weka.gui.treevisualizer.TreeBuild
  Upon construction this will only setup the color table for quick reference of a color.
TreeDisplayEvent - Class in weka.gui.treevisualizer
  An event containing the user selection from the tree display
TreeDisplayEvent(int, String) - Constructor for class weka.gui.treevisualizer.TreeDisplayEvent
  Constructs an event with the specified command and what the command is applied to.
TreeDisplayListener - Interface in weka.gui.treevisualizer
  Interface implemented by classes that wish to recieve user selection events from a tree displayer.
treeErrors() - Method in class weka.classifiers.trees.lmt.LMTNode
  Updates the numIncorrectTree field for all nodes.
treeToString(int) - Method in class weka.classifiers.trees.m5.RuleNode
  Recursively builds a textual description of the tree
TreeVisualizer - Class in weka.gui.treevisualizer
  Class for displaying a Node structure in Swing.
TreeVisualizer(TreeDisplayListener, String, NodePlace) - Constructor for class weka.gui.treevisualizer.TreeVisualizer
  Constructs Displayer to display a tree provided in a dot format.
TreeVisualizer(TreeDisplayListener, Node, NodePlace) - Constructor for class weka.gui.treevisualizer.TreeVisualizer
  Constructs Displayer with the specified Node as the top of the tree, and uses the NodePlacer to place the Nodes.
TRIANGLEDOWN_SHAPE - Static variable in class weka.gui.visualize.Plot2D
TRIANGLEUP_SHAPE - Static variable in class weka.gui.visualize.Plot2D
trim(DoubleVector) - Method in class weka.classifiers.functions.pace.ChisqMixture
  Trims the small values of the estaimte
trim(DoubleVector) - Method in class weka.classifiers.functions.pace.NormalMixture
  Trims the small values of the estaimte
trimToSize() - Method in class weka.core.FastVector
  Sets the vector's capacity to its size.
TRUE_NEG_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve
TRUE_POS_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve
trueNegativeRate(int) - Method in class weka.classifiers.Evaluation
  Calculate the true negative rate with respect to a particular class.
truePositiveRate(int) - Method in class weka.classifiers.Evaluation
  Calculate the true positive rate with respect to a particular class.
TStartTipText() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
TStartTipText() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
turnChecksOff() - Method in class weka.classifiers.functions.LinearRegression
  Turns off checks for missing values, etc.
turnChecksOff() - Method in class weka.classifiers.functions.SMO
  Turns off checks for missing values, etc.
turnChecksOff() - Method in class weka.classifiers.functions.SMOreg
  Turns off checks for missing values, etc.
turnChecksOn() - Method in class weka.classifiers.functions.LinearRegression
  Turns on checks for missing values, etc.
turnChecksOn() - Method in class weka.classifiers.functions.SMO
  Turns on checks for missing values, etc.
turnChecksOn() - Method in class weka.classifiers.functions.SMOreg
  Turns on checks for missing values, etc.
TwoClassStats - Class in weka.classifiers.evaluation
  Encapsulates performance functions for two-class problems.
TwoClassStats(double, double, double, double) - Constructor for class weka.classifiers.evaluation.TwoClassStats
  Creates the TwoClassStats with the given initial performance values.
TwoWayNominalSplit - Class in weka.classifiers.trees.adtree
  Class representing a two-way split on a nominal attribute, of the form: either 'is some_value' or 'is not some_value'.
TwoWayNominalSplit(int, int) - Constructor for class weka.classifiers.trees.adtree.TwoWayNominalSplit
  Creates a new two-way nominal splitter.
TwoWayNumericSplit - Class in weka.classifiers.trees.adtree
  Class representing a two-way split on a numeric attribute, of the form: either 'is < some_value' or 'is >= some_value'.
TwoWayNumericSplit(int, double) - Constructor for class weka.classifiers.trees.adtree.TwoWayNumericSplit
  Creates a new two-way numeric splitter.
type() - Method in class weka.core.Attribute
  Returns the attribute's type as an integer.
typeName(int) - Static method in class weka.experiment.DatabaseUtils
  Returns the name associated with a SQL type.

## U

uminus() - Method in class weka.classifiers.functions.pace.Matrix
  Unary minus
uminus() - Method in class weka.core.matrix.Matrix
  Unary minus
UnassignedClassException - Exception in weka.core
  Exception that is raised when trying to use some data that has no class assigned to it, but a class is needed to perform the operation.
UnassignedClassException() - Constructor for exception weka.core.UnassignedClassException
  Creates a new UnassignedClassException with no message.
UnassignedClassException(String) - Constructor for exception weka.core.UnassignedClassException
  Creates a new UnassignedClassException.
UnassignedDatasetException - Exception in weka.core
  Exception that is raised when trying to use something that has no reference to a dataset, when one is required.
UnassignedDatasetException() - Constructor for exception weka.core.UnassignedDatasetException
  Creates a new UnassignedDatasetException with no message.
UnassignedDatasetException(String) - Constructor for exception weka.core.UnassignedDatasetException
  Creates a new UnassignedDatasetException.
unbackQuoteChars(String) - Static method in class weka.core.Utils
  The inverse operation of backQuoteChars().
unclassified() - Method in class weka.classifiers.Evaluation
  Gets the number of instances not classified (that is, for which no prediction was made by the classifier).
UNCONNECTED - Static variable in class weka.classifiers.functions.neural.NeuralConnection
  This unit is not connected to any others.
undefinedDistribution - Static variable in class weka.classifiers.functions.pace.Maths
  Distribution type: undefined
undo() - Method in interface weka.core.Undoable
  undoes the last action
undo() - Method in class weka.gui.arffviewer.ArffPanel
  performs an undo action
undo() - Method in class weka.gui.arffviewer.ArffTableModel
  undoes the last action
undo() - Method in class weka.gui.arffviewer.ArffTableSorter
  undoes the last action
undo() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  undoes the last action
undo() - Method in class weka.gui.explorer.PreprocessPanel
  Reverts to the last backed up version of the dataset.
Undoable - Interface in weka.core
  Interface implemented by classes that support undo.
unique() - Method in class weka.classifiers.functions.pace.DiscreteFunction
  Makes each individual point value unique
uniqueCount - Variable in class weka.core.AttributeStats
  The number of values that only appear once
unpivoting(IntVector, int) - Method in class weka.classifiers.functions.pace.DoubleVector
  Returns a vector from the pivoting indices.
unprunedTipText() - Method in class weka.classifiers.rules.PART
  Returns the tip text for this property
unprunedTipText() - Method in class weka.classifiers.trees.J48
  Returns the tip text for this property
unsorted() - Method in class weka.classifiers.functions.pace.DoubleVector
  Returns true if vector not sorted
UnsupervisedAttributeEvaluator - Class in weka.attributeSelection
  Abstract unsupervised attribute evaluator.
UnsupervisedAttributeEvaluator() - Constructor for class weka.attributeSelection.UnsupervisedAttributeEvaluator
UnsupervisedFilter - Interface in weka.filters
  Interface for filters that do not need a class attribute.
UnsupervisedSubsetEvaluator - Class in weka.attributeSelection
  Abstract unsupervised attribute subset evaluator.
UnsupervisedSubsetEvaluator() - Constructor for class weka.attributeSelection.UnsupervisedSubsetEvaluator
UnsupportedAttributeTypeException - Exception in weka.core
  Exception that is raised by an object that is unable to process some of the attribute types it has been passed.
UnsupportedAttributeTypeException() - Constructor for exception weka.core.UnsupportedAttributeTypeException
  Creates a new UnsupportedAttributeTypeException with no message.
UnsupportedAttributeTypeException(String) - Constructor for exception weka.core.UnsupportedAttributeTypeException
  Creates a new UnsupportedAttributeTypeException.
UnsupportedClassTypeException - Exception in weka.core
  Exception that is raised by an object that is unable to process the class type of the data it has been passed.
UnsupportedClassTypeException() - Constructor for exception weka.core.UnsupportedClassTypeException
  Creates a new UnsupportedClassTypeException with no message.
UnsupportedClassTypeException(String) - Constructor for exception weka.core.UnsupportedClassTypeException
  Creates a new UnsupportedClassTypeException.
upDate(Instances) - Method in class weka.associations.tertius.LiteralSet
  Update the number of counter-instances of this set in the dataset.
upDate(Instances) - Method in class weka.associations.tertius.Rule
  Update the number of counter-instances of this rule in the dataset.
update(double) - Method in class weka.classifiers.functions.pace.FlexibleDecimalFormat
update(Graphics) - Method in class weka.gui.SplashWindow
  Updates the display area of the window.
UpdateableClassifier - Interface in weka.classifiers
  Interface to incremental classification models that can learn using one instance at a time.
updateChildPropertySheet() - Method in class weka.gui.GenericObjectEditor.GOEPanel
  Updates the child property sheet, and creates if needed
updateClassifier(Instance) - Method in class weka.classifiers.bayes.AODE
  Updates the classifier with the given instance.
updateClassifier(Instance) - Method in class weka.classifiers.bayes.BayesNet
  Updates the classifier with the given instance.
updateClassifier(Instance) - Method in class weka.classifiers.bayes.NaiveBayes
  Updates the classifier with the given instance.
updateClassifier(BayesNet, Instance) - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator
  Updates the classifier with the given instance.
updateClassifier(BayesNet, Instance) - Method in class weka.classifiers.bayes.net.estimate.BMAEstimator
  Updates the classifier with the given instance.
updateClassifier(BayesNet, Instance) - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator
  Updates the classifier with the given instance.
updateClassifier(BayesNet, Instance) - Method in class weka.classifiers.bayes.net.estimate.SimpleEstimator
  Updates the classifier with the given instance.
updateClassifier(Instance) - Method in class weka.classifiers.functions.Winnow
  Updates the classifier with a new learning example
updateClassifier(Instance) - Method in class weka.classifiers.lazy.IB1
  Updates the classifier.
updateClassifier(Instance) - Method in class weka.classifiers.lazy.IBk
  Adds the supplied instance to the training set
updateClassifier(Instance) - Method in class weka.classifiers.lazy.KStar
  Adds the supplied instance to the training set
updateClassifier(Instance) - Method in class weka.classifiers.lazy.LWL
  Adds the supplied instance to the training set
updateClassifier(Instance) - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost
  Updates the classifier.
updateClassifier(Instance) - Method in class weka.classifiers.misc.HyperPipes
  Updates the classifier.
updateClassifier(Instance) - Method in class weka.classifiers.rules.NNge
  Updates the classifier using the given instance.
updateClassifier(Instance) - Method in interface weka.classifiers.UpdateableClassifier
  Updates a classifier using the given instance.
upDateCounter(Instance) - Method in class weka.associations.ItemSet
  Updates counter of item set with respect to given transaction.
upDateCounter(Instance, Instance) - Method in class weka.associations.LabeledItemSet
  Updates counter of item set with respect to given transaction.
upDateCounters(FastVector, Instances) - Static method in class weka.associations.ItemSet
  Updates counters for a set of item sets and a set of instances.
upDateCounters(FastVector, Instances, Instances) - Static method in class weka.associations.LabeledItemSet
  Updates counter of a specific item set
updateCounters(ItemSet) - Method in class weka.associations.PriorEstimation
  updates the support count of an item set
updateFrameTitle() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
  sets the title of the parent frame, if one was provided
updatePriors(Instance) - Method in class weka.classifiers.Evaluation
  Updates the class prior probabilities (when incrementally training)
updateResult(String) - Method in class weka.gui.ResultHistoryPanel
  Tells any component currently displaying the named result that the contents of the result text in the StringBuffer have been updated.
updateWeights(NeuralNode, double, double) - Method in class weka.classifiers.functions.neural.LinearUnit
  This function will calculate what the change in weights should be and also update them.
updateWeights(double, double) - Method in class weka.classifiers.functions.neural.NeuralConnection
  Call this function to update the weight values at this unit.
updateWeights(NeuralNode, double, double) - Method in interface weka.classifiers.functions.neural.NeuralMethod
  This function will calculate what the change in weights should be and also update them.
updateWeights(double, double) - Method in class weka.classifiers.functions.neural.NeuralNode
  Call this function to update the weight values at this unit.
updateWeights(NeuralNode, double, double) - Method in class weka.classifiers.functions.neural.SigmoidUnit
  This function will calculate what the change in weights should be and also update them.
upperBoundMinSupportTipText() - Method in class weka.associations.Apriori
  Returns the tip text for this property
upperNumericBoundIsOpen() - Method in class weka.core.Attribute
  Returns whether the upper numeric bound of the attribute is open.
upperSizeTipText() - Method in class weka.experiment.LearningRateResultProducer
  Returns the tip text for this property
urlTipText() - Method in class weka.core.converters.DatabaseLoader
  the tip text for this property
urlTipText() - Method in class weka.core.converters.DatabaseSaver
  Returns the tip text fo this property
useADTreeTipText() - Method in class weka.classifiers.bayes.BayesNet
useArcReversalTipText() - Method in class weka.classifiers.bayes.net.search.global.HillClimber
useArcReversalTipText() - Method in class weka.classifiers.bayes.net.search.local.HillClimber
useBetterEncodingTipText() - Method in class weka.filters.supervised.attribute.Discretize
  Returns the tip text for this property
useCrossOverTipText() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
useCrossOverTipText() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
useCrossValidationTipText() - Method in class weka.classifiers.functions.SimpleLogistic
  Returns the tip text for this property
useDefaultVisual() - Method in class weka.gui.beans.AbstractDataSink
  Use the default images for a data source
useDefaultVisual() - Method in class weka.gui.beans.AbstractDataSource
  Use the default images for a data source
useDefaultVisual() - Method in class weka.gui.beans.AbstractEvaluator
  Use the default images for an evaluator
useDefaultVisual() - Method in class weka.gui.beans.AbstractTestSetProducer
  Use the default visual for this bean
useDefaultVisual() - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer
  Use the default visual for this bean
useDefaultVisual() - Method in class weka.gui.beans.AbstractTrainingSetProducer
  Use the default visual for this bean
useDefaultVisual() - Method in class weka.gui.beans.AttributeSummarizer
  Use the default appearance for this bean
useDefaultVisual() - Method in class weka.gui.beans.ClassAssigner
useDefaultVisual() - Method in class weka.gui.beans.Classifier
  Use the default visual appearance for this bean
useDefaultVisual() - Method in class weka.gui.beans.ClassValuePicker
useDefaultVisual() - Method in class weka.gui.beans.Clusterer
  Use the default visual appearance for this bean
useDefaultVisual() - Method in class weka.gui.beans.DataVisualizer
  Use the default appearance for this bean
useDefaultVisual() - Method in class weka.gui.beans.Filter
  Use the default visual appearance
useDefaultVisual() - Method in class weka.gui.beans.GraphViewer
  Use the default visual appearance
useDefaultVisual() - Method in class weka.gui.beans.MetaBean
  Use the default visual appearance for this bean
useDefaultVisual() - Method in class weka.gui.beans.ModelPerformanceChart
  Use the default appearance for this bean
useDefaultVisual() - Method in class weka.gui.beans.PredictionAppender
  Use the default images for a data source
useDefaultVisual() - Method in class weka.gui.beans.StripChart
  Use the default visual appearance for this bean
useDefaultVisual() - Method in class weka.gui.beans.TextViewer
  Use the default visual appearance for this bean
useDefaultVisual() - Method in interface weka.gui.beans.Visible
  Use the default visual representation
useEqualFrequencyTipText() - Method in class weka.filters.unsupervised.attribute.Discretize
  Returns the tip text for this property
useEqualFrequencyTipText() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize
  Returns the tip text for this property
useFilter(Instances, Filter) - Static method in class weka.filters.Filter
  Filters an entire set of instances through a filter and returns the new set.
useIBkTipText() - Method in class weka.classifiers.rules.DecisionTable
  Returns the tip text for this property
useKernelEstimatorTipText() - Method in class weka.classifiers.bayes.NaiveBayes
  Returns the tip text for this property
useKononenkoTipText() - Method in class weka.filters.supervised.attribute.Discretize
  Returns the tip text for this property
useLaplaceTipText() - Method in class weka.classifiers.trees.J48
  Returns the tip text for this property
useMissingTipText() - Method in class weka.filters.unsupervised.attribute.AddNoise
  Returns the tip text for this property
useMutationTipText() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
useMutationTipText() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
useNoPriors() - Method in class weka.classifiers.Evaluation
  disables the use of priors, e.g., in case of de-serialized schemes that have no access to the original training set, but are evaluated on a set set.
useProbTipText() - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
usePruningTipText() - Method in class weka.classifiers.rules.JRip
  Returns the tip text for this property
useRBFTipText() - Method in class weka.classifiers.functions.SMO
  Returns the tip text for this property
useRBFTipText() - Method in class weka.classifiers.functions.SMOreg
  Returns the tip text for this property
UserClassifier - Class in weka.classifiers.trees
  Class for generating an user defined decision tree.
UserClassifier() - Constructor for class weka.classifiers.trees.UserClassifier
  Constructor
userCommand(TreeDisplayEvent) - Method in class weka.classifiers.trees.UserClassifier
  Receives user choices from the tree view, and then deals with these choices.
userCommand(TreeDisplayEvent) - Method in interface weka.gui.treevisualizer.TreeDisplayListener
  Gets called when the user selects something, in the tree display.
userDataEvent(VisualizePanelEvent) - Method in class weka.classifiers.trees.UserClassifier
  This receives shapes from the data view.
userDataEvent(VisualizePanelEvent) - Method in interface weka.gui.visualize.VisualizePanelListener
  This method receives an object containing the shapes, instances inside and outside these shapes and the attributes these shapes were created in.
useResamplingTipText() - Method in class weka.classifiers.meta.AdaBoostM1
  Returns the tip text for this property
useResamplingTipText() - Method in class weka.classifiers.meta.LogitBoost
  Returns the tip text for this property
useResamplingTipText() - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost
usernameTipText() - Method in class weka.experiment.DatabaseUtils
  Returns the tip text for this property
UserRequestAcceptor - Interface in weka.gui.beans
  Interface to something that can accept requests from a user to perform some action
userTipText() - Method in class weka.core.converters.DatabaseLoader
  the tip text for this property
userTipText() - Method in class weka.core.converters.DatabaseSaver
  Returns the tip text fo this property
useStoplistTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Returns the tip text for this property.
useSupervisedDiscretizationTipText() - Method in class weka.classifiers.bayes.NaiveBayes
  Returns the tip text for this property
useTournamentSelectionTipText() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
useTournamentSelectionTipText() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
useTrainingTipText() - Method in class weka.attributeSelection.ClassifierSubsetEval
  Returns the tip text for this property
Utils - Class in weka.core
  Class implementing some simple utility methods.
Utils() - Constructor for class weka.core.Utils

## V

VAL_ANIMATEDICONPATH - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the animatedIconPath property
VAL_ASSOCIATEDCONNECTIONS - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the associatedConnections property
VAL_BEAN - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the bean property
VAL_BEANCONTEXT - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the beanContext property
VAL_BLUE - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the blue property
VAL_CELLS - Static variable in class weka.core.xml.XMLBasicSerialization
  the matrix cells
VAL_COLOR - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the color property
VAL_DIR - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the dir property
VAL_EVENTNAME - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the eventname property
VAL_FILE - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the file property
VAL_FONT - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the font property
VAL_GREEN - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the green property
VAL_HEIGHT - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the height property
VAL_HIDDEN - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the hidden property
VAL_ICONPATH - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the iconpath property
VAL_ID - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the id property
VAL_INPUTS - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the input property
VAL_INPUTSID - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the input id property
VAL_KEY - Static variable in class weka.core.xml.XMLBasicSerialization
  the value for a mapping-key, e.g., Maps
VAL_LOADER - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the loader property
VAL_LOCATION - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the location property
VAL_MAPPING - Static variable in class weka.core.xml.XMLBasicSerialization
  the value for mapping, e.g., Maps
VAL_NAME - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the value property
VAL_NO - Static variable in class weka.core.xml.XMLSerialization
  the value "no" for the primitive and array attribute
VAL_OPTIONS - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the options property
VAL_ORIGINALCOORDS - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the originalCoords property
VAL_OUTPUTS - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the outputs id property
VAL_OUTPUTSID - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the outputs property
VAL_PREFIX - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the prefix property
VAL_RED - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the red property
VAL_ROOT - Static variable in class weka.core.xml.XMLSerialization
  the value of the name for the root node
VAL_SAVER - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the saver property
VAL_SIZE - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the size property
VAL_SOURCEID - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the source property
VAL_STYLE - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the style property
VAL_SUBFLOW - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the subFlow property
VAL_TARGETID - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the target property
VAL_TEXT - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the text property
VAL_TYPE_CLASSIFIER - Static variable in class weka.core.xml.XMLOptions
  a value of the type attribute
VAL_TYPE_FLAG - Static variable in class weka.core.xml.XMLOptions
  a value of the type attribute
VAL_TYPE_HYPHENS - Static variable in class weka.core.xml.XMLOptions
  a value of the type attribute
VAL_TYPE_QUOTES - Static variable in class weka.core.xml.XMLOptions
  a value of the type attribute
VAL_TYPE_SINGLE - Static variable in class weka.core.xml.XMLOptions
  a value of the type attribute
VAL_VALUE - Static variable in class weka.core.xml.XMLBasicSerialization
  the value for mapping-value, e.g., Maps
VAL_WIDTH - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the width property
VAL_X - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the x property
VAL_Y - Static variable in class weka.gui.beans.xml.XMLBeans
  the value of the y property
VAL_YES - Static variable in class weka.core.xml.XMLSerialization
  the value "yes" for the primitive and array attribute
validationChunkSizeTipText() - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost
validationSetSizeTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
validationThresholdTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
value - Variable in class weka.classifiers.lazy.kstar.KStarCache.TableEntry
  scale factor or stop parameter
value(int) - Method in class weka.core.Attribute
  Returns a value of a nominal or string attribute.
value(int) - Method in class weka.core.BinarySparseInstance
  Returns an instance's attribute value in internal format.
value(int) - Method in class weka.core.Instance
  Returns an instance's attribute value in internal format.
value(Attribute) - Method in class weka.core.Instance
  Returns an instance's attribute value in internal format.
value(int) - Method in class weka.core.SparseInstance
  Returns an instance's attribute value in internal format.
value - Variable in class weka.experiment.PropertyNode
  The current property value
valueIndicesTipText() - Method in class weka.filters.unsupervised.attribute.MakeIndicator
Values - Class in weka.classifiers.trees.m5
  Stores some statistics.
Values(int, int, int, Instances) - Constructor for class weka.classifiers.trees.m5.Values
  Constructs an object which stores some statistics of the instances such as sum, squared sum, variance, standard deviation
valuesOutputTipText() - Method in class weka.associations.Tertius
  Returns the tip text for this property.
valueSparse(int) - Method in class weka.core.BinarySparseInstance
  Returns an instance's attribute value in internal format.
valueSparse(int) - Method in class weka.core.Instance
  Returns an instance's attribute value in internal format.
valuesToString() - Method in class weka.associations.tertius.Rule
  Return a String giving the confirmation and optimistic estimate of this rule.
variance(int) - Method in class weka.core.Instances
  Computes the variance for a numeric attribute.
variance(Attribute) - Method in class weka.core.Instances
  Computes the variance for a numeric attribute.
variance(double[]) - Static method in class weka.core.Utils
  Computes the variance for an array of doubles.
varianceCoveredTipText() - Method in class weka.attributeSelection.PrincipalComponents
  Returns the tip text for this property
VaryNode - Class in weka.classifiers.bayes.net
  Part of ADTree implementation.
VaryNode(int) - Constructor for class weka.classifiers.bayes.net.VaryNode
  Creates new VaryNode
VERBOSE - Static variable in class weka.core.RTSI
  whether to output some debug information
VERBOSE - Static variable in class weka.gui.GenericPropertiesCreator
  whether to output some debug information
verboseTipText() - Method in class weka.associations.Apriori
  Returns the tip text for this property
verboseTipText() - Method in class weka.attributeSelection.ExhaustiveSearch
  Returns the tip text for this property
verboseTipText() - Method in class weka.attributeSelection.RandomSearch
  Returns the tip text for this property
Version - Class in weka.core
  This class contains the version number of the current WEKA release and some methods for comparing another version string.
Version() - Constructor for class weka.core.Version
VERSION - Static variable in class weka.core.Version
  the complete version
VFI - Class in weka.classifiers.misc
  Class implementing the voting feature interval classifier.
VFI() - Constructor for class weka.classifiers.misc.VFI
ViewerDialog - Class in weka.gui
  A downsized version of the ArffViewer, displaying only one Instances-Object.
ViewerDialog(Frame) - Constructor for class weka.gui.ViewerDialog
  initializes the dialog with the given parent
Visible - Interface in weka.gui.beans
  Interface to something that has a visible (via BeanVisual) reprentation
VisualizableErrorEvent - Class in weka.gui.beans
  Event encapsulating error information for a learning scheme that can be visualized in the DataVisualizer
VisualizableErrorEvent(Object, PlotData2D) - Constructor for class weka.gui.beans.VisualizableErrorEvent
VisualizableErrorListener - Interface in weka.gui.beans
  Interface to something that can accept VisualizableErrorEvents
VisualizePanel - Class in weka.gui.visualize
  This panel allows the user to visualize a dataset (and if provided) a classifier's/clusterer's predictions in two dimensions.
VisualizePanel(VisualizePanelListener) - Constructor for class weka.gui.visualize.VisualizePanel
  This constructor allows a VisualizePanelListener to be set.
VisualizePanel() - Constructor for class weka.gui.visualize.VisualizePanel
  Constructor
VisualizePanelEvent - Class in weka.gui.visualize
  This event Is fired to a listeners 'userDataEvent' function when The user on the VisualizePanel clicks submit.
VisualizePanelEvent(FastVector, Instances, Instances, int, int) - Constructor for class weka.gui.visualize.VisualizePanelEvent
  This constructor creates the event with all the parameters set.
VisualizePanelListener - Interface in weka.gui.visualize
  Interface implemented by a class that is interested in receiving submited shapes from a visualize panel.
VisualizeUtils - Class in weka.gui.visualize
  This class contains utility routines for visualization
VisualizeUtils() - Constructor for class weka.gui.visualize.VisualizeUtils
VLINE - Static variable in class weka.gui.visualize.VisualizePanelEvent
Vote - Class in weka.classifiers.meta
  Class for combining classifiers using unweighted average of probability estimates (classification) or numeric predictions (regression).
Vote() - Constructor for class weka.classifiers.meta.Vote
VotedPerceptron - Class in weka.classifiers.functions
  Implements the voted perceptron algorithm by Freund and Schapire.
VotedPerceptron() - Constructor for class weka.classifiers.functions.VotedPerceptron

## W

weight() - Method in class weka.classifiers.evaluation.NominalPrediction
  Gets the weight assigned to this prediction.
weight() - Method in class weka.classifiers.evaluation.NumericPrediction
  Gets the weight assigned to this prediction.
weight() - Method in interface weka.classifiers.evaluation.Prediction
  Gets the weight assigned to this prediction.
weight(Instance) - Method in class weka.classifiers.rules.part.ClassifierDecList
  Returns the weight a rule assigns to an instance.
weight() - Method in class weka.core.Attribute
  Returns the attribute's weight.
weight() - Method in class weka.core.Instance
  Returns the instance's weight.
WEIGHT_INVERSE - Static variable in class weka.classifiers.lazy.IBk
WEIGHT_NONE - Static variable in class weka.classifiers.lazy.IBk
WEIGHT_SIMILARITY - Static variable in class weka.classifiers.lazy.IBk
weightByConfidenceTipText() - Method in class weka.classifiers.misc.VFI
  Returns the tip text for this property
weightByDistanceTipText() - Method in class weka.attributeSelection.ReliefFAttributeEval
  Returns the tip text for this property
WeightedInstancesHandler - Interface in weka.core
  Interface to something that makes use of the information provided by instance weights.
weightingKernelTipText() - Method in class weka.classifiers.lazy.LWL
  Returns the tip text for this property
weights(Instance) - Method in class weka.classifiers.trees.j48.BinC45Split
  Returns weights if instance is assigned to more than one subset.
weights(Instance) - Method in class weka.classifiers.trees.j48.C45Split
  Returns weights if instance is assigned to more than one subset.
weights(Instance) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
  Returns weights if instance is assigned to more than one subset.
weights(Instance) - Method in class weka.classifiers.trees.j48.NBTreeNoSplit
  Always returns null because there is only one subset.
weights(Instance) - Method in class weka.classifiers.trees.j48.NBTreeSplit
  Returns weights if instance is assigned to more than one subset.
weights(Instance) - Method in class weka.classifiers.trees.j48.NoSplit
  Always returns null because there is only one subset.
weights(Instance) - Method in class weka.classifiers.trees.lmt.ResidualSplit
  Method not in use
weightThresholdTipText() - Method in class weka.classifiers.meta.AdaBoostM1
  Returns the tip text for this property
weightThresholdTipText() - Method in class weka.classifiers.meta.LogitBoost
  Returns the tip text for this property
weightValue(int) - Method in class weka.classifiers.functions.neural.NeuralConnection
  Call this to get the weight value on a particular connection.
weightValue(int) - Method in class weka.classifiers.functions.neural.NeuralNode
  Call this to get the weight value on a particular connection.
weka.associations - package weka.associations
weka.associations.tertius - package weka.associations.tertius
weka.attributeSelection - package weka.attributeSelection
weka.classifiers - package weka.classifiers
weka.classifiers.bayes - package weka.classifiers.bayes
weka.classifiers.bayes.net - package weka.classifiers.bayes.net
weka.classifiers.bayes.net.estimate - package weka.classifiers.bayes.net.estimate
weka.classifiers.bayes.net.search - package weka.classifiers.bayes.net.search
weka.classifiers.bayes.net.search.ci - package weka.classifiers.bayes.net.search.ci
weka.classifiers.bayes.net.search.fixed - package weka.classifiers.bayes.net.search.fixed
weka.classifiers.bayes.net.search.global - package weka.classifiers.bayes.net.search.global
weka.classifiers.bayes.net.search.local - package weka.classifiers.bayes.net.search.local
weka.classifiers.evaluation - package weka.classifiers.evaluation
weka.classifiers.functions - package weka.classifiers.functions
weka.classifiers.functions.neural - package weka.classifiers.functions.neural
weka.classifiers.functions.pace - package weka.classifiers.functions.pace
weka.classifiers.functions.supportVector - package weka.classifiers.functions.supportVector
weka.classifiers.lazy - package weka.classifiers.lazy
weka.classifiers.lazy.kstar - package weka.classifiers.lazy.kstar
weka.classifiers.meta - package weka.classifiers.meta
weka.classifiers.misc - package weka.classifiers.misc
weka.classifiers.rules - package weka.classifiers.rules
weka.classifiers.rules.part - package weka.classifiers.rules.part
weka.classifiers.trees - package weka.classifiers.trees
weka.classifiers.trees.adtree - package weka.classifiers.trees.adtree
weka.classifiers.trees.j48 - package weka.classifiers.trees.j48
weka.classifiers.trees.lmt - package weka.classifiers.trees.lmt
weka.classifiers.trees.m5 - package weka.classifiers.trees.m5
weka.classifiers.xml - package weka.classifiers.xml
weka.clusterers - package weka.clusterers
weka.core - package weka.core
weka.core.converters - package weka.core.converters
weka.core.matrix - package weka.core.matrix
weka.core.xml - package weka.core.xml
weka.datagenerators - package weka.datagenerators
weka.estimators - package weka.estimators
weka.experiment - package weka.experiment
weka.experiment.xml - package weka.experiment.xml
weka.filters - package weka.filters
weka.filters.supervised.attribute - package weka.filters.supervised.attribute
weka.filters.supervised.instance - package weka.filters.supervised.instance
weka.filters.unsupervised.attribute - package weka.filters.unsupervised.attribute
weka.filters.unsupervised.instance - package weka.filters.unsupervised.instance
weka.gui - package weka.gui
weka.gui.arffviewer - package weka.gui.arffviewer
weka.gui.beans - package weka.gui.beans
weka.gui.beans.xml - package weka.gui.beans.xml
weka.gui.boundaryvisualizer - package weka.gui.boundaryvisualizer
weka.gui.experiment - package weka.gui.experiment
weka.gui.explorer - package weka.gui.explorer
weka.gui.graphvisualizer - package weka.gui.graphvisualizer
weka.gui.streams - package weka.gui.streams
weka.gui.treevisualizer - package weka.gui.treevisualizer
weka.gui.visualize - package weka.gui.visualize
WekaException - Exception in weka.core
  Class for Weka-specific exceptions.
WekaException() - Constructor for exception weka.core.WekaException
  Creates a new WekaException with no message.
WekaException(String) - Constructor for exception weka.core.WekaException
  Creates a new WekaException.
WekaTaskMonitor - Class in weka.gui
  This panel records the number of weka tasks running and displays a simple bird animation while their are active tasks
WekaTaskMonitor() - Constructor for class weka.gui.WekaTaskMonitor
  Constructor
WekaWrapper - Interface in weka.gui.beans
  Interface to something that can wrap around a class of Weka algorithms (classifiers, filters etc).
WEST_CONNECTOR - Static variable in class weka.gui.beans.BeanVisual
whichSubset(Instance) - Method in class weka.classifiers.trees.j48.BinC45Split
  Returns index of subset instance is assigned to.
whichSubset(Instance) - Method in class weka.classifiers.trees.j48.C45Split
  Returns index of subset instance is assigned to.
whichSubset(Instance) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
  Returns index of subset instance is assigned to.
whichSubset(Instance) - Method in class weka.classifiers.trees.j48.NBTreeNoSplit
  Always returns 0 because only there is only one subset.
whichSubset(Instance) - Method in class weka.classifiers.trees.j48.NBTreeSplit
  Returns index of subset instance is assigned to.
whichSubset(Instance) - Method in class weka.classifiers.trees.j48.NoSplit
  Always returns 0 because only there is only one subset.
whichSubset(Instance) - Method in class weka.classifiers.trees.lmt.ResidualSplit
wholeDataErrTipText() - Method in class weka.classifiers.rules.Ridor
  Returns the tip text for this property
width() - Method in class weka.classifiers.functions.pace.ExponentialFormat
width() - Method in class weka.classifiers.functions.pace.FlexibleDecimalFormat
width() - Method in class weka.classifiers.functions.pace.FloatingPointFormat
WIDTH - Static variable in class weka.gui.arffviewer.ArffViewerMainPanel
  default width
windowActivated(WindowEvent) - Method in class weka.gui.arffviewer.ArffViewer
  invoked when a window is activated
windowClosed(WindowEvent) - Method in class weka.gui.arffviewer.ArffViewer
  invoked when a window is closed
windowClosing(WindowEvent) - Method in class weka.gui.arffviewer.ArffViewer
  invoked when a window is in the process of closing
windowDeactivated(WindowEvent) - Method in class weka.gui.arffviewer.ArffViewer
  invoked when a window is deactivated
windowDeiconified(WindowEvent) - Method in class weka.gui.arffviewer.ArffViewer
  invoked when a window is deiconified
windowIconified(WindowEvent) - Method in class weka.gui.arffviewer.ArffViewer
  invoked when a window is iconified
windowOpened(WindowEvent) - Method in class weka.gui.arffviewer.ArffViewer
  invoked when a window is has been opened
windowSizeTipText() - Method in class weka.classifiers.lazy.IBk
  Returns the tip text for this property
Winnow - Class in weka.classifiers.functions
  Implements Winnow and Balanced Winnow algorithms by N.
Winnow() - Constructor for class weka.classifiers.functions.Winnow
WITHIN_BATCH - Static variable in class weka.gui.beans.IncrementalClassifierEvent
wordsToKeepTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
  Returns the tip text for this property
WrapperSubsetEval - Class in weka.attributeSelection
  Wrapper attribute subset evaluator.
WrapperSubsetEval() - Constructor for class weka.attributeSelection.WrapperSubsetEval
  Constructor.
write(Writer) - Method in class weka.core.matrix.Matrix
  Writes out a matrix.
write(Writer) - Method in class weka.core.Matrix
  Deprecated. Writes out a matrix.
write(String, Object) - Static method in class weka.core.xml.KOML
  writes the XML-serialized object to the given file
write(File, Object) - Static method in class weka.core.xml.KOML
  write the XML-serialized object to the given file
write(OutputStream, Object) - Static method in class weka.core.xml.KOML
  writes the XML-serialized object to a stream
write(String) - Method in class weka.core.xml.XMLDocument
  writes the current DOM document into the given file
write(File) - Method in class weka.core.xml.XMLDocument
  writes the current DOM document into the given file
write(OutputStream) - Method in class weka.core.xml.XMLDocument
  writes the current DOM document into the given stream
write(Writer) - Method in class weka.core.xml.XMLDocument
  writes the current DOM document into the given writer
write(String, Object) - Method in class weka.core.xml.XMLSerialization
  writes the given object into the file
write(File, Object) - Method in class weka.core.xml.XMLSerialization
  writes the given object into the file
write(OutputStream, Object) - Method in class weka.core.xml.XMLSerialization
  writes the given object into the stream
write(Writer, Object) - Method in class weka.core.xml.XMLSerialization
  writes the given object into the writer
write() - Method in class weka.core.xml.XMLSerializationMethodHandler
  returns the handler for write methods
writeBatch() - Method in class weka.core.converters.AbstractSaver
  Writes to a file in batch mode To be overridden.
writeBatch() - Method in class weka.core.converters.ArffSaver
  Writes a Batch of instances
writeBatch() - Method in class weka.core.converters.C45Saver
  Writes a Batch of instances
writeBatch() - Method in class weka.core.converters.CSVSaver
  Writes a Batch of instances
writeBatch() - Method in class weka.core.converters.DatabaseSaver
  Writes a Batch of instances
writeBatch() - Method in interface weka.core.converters.Saver
  Writes to a destination in batch mode
writeBatch() - Method in class weka.core.converters.SerializedInstancesSaver
  Writes a Batch of instances
writeBeanConnection(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans
  adds the given BeanConncetion to a DOM structure.
writeBeanInstance(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans
  adds the given BeanInstance to a DOM structure.
writeBeanLoader(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans
  adds the given Loader (a bean) to a DOM structure.
writeBeanSaver(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans
  adds the given Saver (a bean) to a DOM structure.
writeBeanVisual(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans
  adds the given BeanVisual to a DOM structure.
writeCollection(Element, Object, String) - Method in class weka.core.xml.XMLBasicSerialization
  adds the given Collection to a DOM structure.
writeColor(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans
  adds the given Color to a DOM structure.
writeColorUIResource(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans
  adds the given ColorUIResource to a DOM structure.
writeCostMatrixOld(Element, Object, String) - Method in class weka.core.xml.XMLBasicSerialization
  adds the given CostMatrix (old) to a DOM structure.
writeDefaultListModel(Element, Object, String) - Method in class weka.core.xml.XMLBasicSerialization
  adds the given DefaultListModel to a DOM structure.
writeDimension(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans
  adds the given Dimension to a DOM structure.
writeDOT(String, String, FastVector, FastVector) - Static method in class weka.gui.graphvisualizer.DotParser
  This method saves a graph in a file in DOT format.
writeFont(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans
  adds the given Font to a DOM structure.
writeFontUIResource(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans
  adds the given FontUIResource to a DOM structure.
writeIncremental(Instance) - Method in class weka.core.converters.AbstractSaver
  Method for incremental saving.
writeIncremental(Instance) - Method in class weka.core.converters.ArffSaver
  Saves an instances incrementally.
writeIncremental(Instance) - Method in class weka.core.converters.C45Saver
  Saves an instances incrementally.
writeIncremental(Instance) - Method in class weka.core.converters.CSVSaver
  Saves an instances incrementally.
writeIncremental(Instance) - Method in class weka.core.converters.DatabaseSaver
  Saves an instances incrementally.
writeIncremental(Instance) - Method in interface weka.core.converters.Saver
  Writes to a destination in incremental mode.
writeLoader(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans
  adds the given Loader to a DOM structure.
writeMap(Element, Object, String) - Method in class weka.core.xml.XMLBasicSerialization
  adds the given Map to a DOM structure.
writeMatrix(Element, Object, String) - Method in class weka.core.xml.XMLBasicSerialization
  adds the given Matrix to a DOM structure.
writeMatrixOld(Element, Object, String) - Method in class weka.core.xml.XMLBasicSerialization
  adds the given Matrix (old) to a DOM structure.
writeMetaBean(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans
  adds the given MetaBean to a DOM structure.
writePoint(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans
  adds the given Point to a DOM structure.
writePropertyNode(Element, Object, String) - Method in class weka.experiment.xml.XMLExperiment
  adds the given PropertyNode to a DOM structure.
writeSaver(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans
  adds the given Saver to a DOM structure.
writeToXML(Element, Object, String) - Method in class weka.core.xml.XMLSerialization
  adds the given Object to a DOM structure.
writeXMLBIF03(String, String, FastVector, FastVector) - Static method in class weka.gui.graphvisualizer.BIFParser
  This method writes a graph in XMLBIF ver.

## X

X_SHAPE - Static variable in class weka.gui.visualize.Plot2D
xLabelFreqTipText() - Method in class weka.gui.beans.StripChart
  GUI Tip text
xlogx(int) - Static method in class weka.core.Utils
  Returns c*log2(c) for a given integer value c.
XMLBasicSerialization - Class in weka.core.xml
  This serializer contains some read/write methods for common classes that are not beans-conform.
XMLBasicSerialization() - Constructor for class weka.core.xml.XMLBasicSerialization
  initializes the serialization
XMLBeans - Class in weka.gui.beans.xml
  This class serializes and deserializes a KnowledgeFlow setup to and fro XML.
XMLBeans(JComponent, BeanContextSupport) - Constructor for class weka.gui.beans.xml.XMLBeans
  initializes the serialization for layouts
XMLBeans(JComponent, BeanContextSupport, int) - Constructor for class weka.gui.beans.xml.XMLBeans
  initializes the serialization for different types of data
XMLClassifier - Class in weka.classifiers.xml
  This class serializes and deserializes a Classifier instance to and fro XML.
XMLClassifier() - Constructor for class weka.classifiers.xml.XMLClassifier
  initializes the serialization
XMLDocument - Class in weka.core.xml
  This class offers some methods for generating, reading and writing XML documents.
  It can only handle UTF-8.
XMLDocument() - Constructor for class weka.core.xml.XMLDocument
  initializes the factory with non-validating parser
XMLDocument(String) - Constructor for class weka.core.xml.XMLDocument
  Creates a new instance of XMLDocument
XMLDocument(File) - Constructor for class weka.core.xml.XMLDocument
  Creates a new instance of XMLDocument
XMLDocument(InputStream) - Constructor for class weka.core.xml.XMLDocument
  Creates a new instance of XMLDocument
XMLDocument(Reader) - Constructor for class weka.core.xml.XMLDocument
  Creates a new instance of XMLDocument
XMLExperiment - Class in weka.experiment.xml
  This class serializes and deserializes an Experiment instance to and fro XML.
  It omits the `options` from the Experiment, since these are handled by the get/set-methods.
XMLExperiment() - Constructor for class weka.experiment.xml.XMLExperiment
  initializes the serialization
XMLOptions - Class in weka.core.xml
  A class for transforming options listed in XML to a regular WEKA command line string.
XMLOptions() - Constructor for class weka.core.xml.XMLOptions
  Creates a new instance of XMLOptions
XMLOptions(String) - Constructor for class weka.core.xml.XMLOptions
  Creates a new instance of XMLOptions
XMLOptions(File) - Constructor for class weka.core.xml.XMLOptions
  Creates a new instance of XMLOptions
XMLOptions(InputStream) - Constructor for class weka.core.xml.XMLOptions
  Creates a new instance of XMLOptions
XMLOptions(Reader) - Constructor for class weka.core.xml.XMLOptions
  Creates a new instance of XMLOptions
XMLSerialization - Class in weka.core.xml
  With this class objects can be serialized to XML instead into a binary format.
XMLSerialization() - Constructor for class weka.core.xml.XMLSerialization
  initializes the serialization
XMLSerializationMethodHandler - Class in weka.core.xml
  This class handles relationships between display names of properties (or classes) and Methods that are associated with them.
XMLSerializationMethodHandler(Object) - Constructor for class weka.core.xml.XMLSerializationMethodHandler
  initializes the method handling, executes also `clear()`, which adds initial methods automatically.
xStats - Variable in class weka.experiment.PairedStats
  The stats associated with the data in column 1
XVALTAGS_SELECTION - Static variable in class weka.attributeSelection.RaceSearch
xySum - Variable in class weka.experiment.PairedStats
  The sum of the products

## Y

YongSplitInfo - Class in weka.classifiers.trees.m5
  Stores split information.
YongSplitInfo(int, int, int) - Constructor for class weka.classifiers.trees.m5.YongSplitInfo
  Constructs an object which contains the split information
yStats - Variable in class weka.experiment.PairedStats
  The stats associated with the data in column 2

## Z

ZeroR - Class in weka.classifiers.rules
  Class for building and using a 0-R classifier.
ZeroR() - Constructor for class weka.classifiers.rules.ZeroR
zipit(String, String) - Method in class weka.experiment.OutputZipper
  Saves a string to either an individual gzipped file or as an entry in a zip file.

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

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