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## weka.classifiers.meta
Class AttributeSelectedClassifier

    java.lang.Object
      weka.classifiers.Classifier
          weka.classifiers.SingleClassifierEnhancer
              weka.classifiers.meta.AttributeSelectedClassifier

All Implemented Interfaces:
  java.io.Serializable, java.lang.Cloneable, AdditionalMeasureProducer, Drawable, OptionHandler, WeightedInstancesHandler

    public class AttributeSelectedClassifier

extends SingleClassifierEnhancer
implements OptionHandler, Drawable, AdditionalMeasureProducer, WeightedInstancesHandler

Class for running an arbitrary classifier on data that has been reduced through attribute selection.

Valid options from the command line are:

-W classifierstring
Classifierstring should contain the full class name of a classifier. Any options for the classifier should appear at the end of the command line following a "--". .

-E evaluatorstring
Evaluatorstring should contain the full class name of an attribute evaluator followed by any options. (required).

-S searchstring
Searchstring should contain the full class name of a search method followed by any options. (required).

Version:
  $Revision: 1.16.2.4 $
Author:
  Mark Hall (mhall@cs.waikato.ac.nz)
See Also:
  Serialized Form

Field Summary

Fields inherited from interface weka.core.Drawable
`BayesNet, NOT_DRAWABLE, TREE`

Constructor Summary
`AttributeSelectedClassifier()` Default constructor.

Method Summary
`void` | `buildClassifier(Instances data)` Build the classifier on the dimensionally reduced data.
`double[]` | `distributionForInstance(Instance instance)` Classifies a given instance after attribute selection
`java.util.Enumeration` | `enumerateMeasures()` Returns an enumeration of the additional measure names
`java.lang.String` | `evaluatorTipText()` Returns the tip text for this property
`ASEvaluation` | `getEvaluator()` Gets the attribute evaluator used
`double` | `getMeasure(java.lang.String additionalMeasureName)` Returns the value of the named measure
`java.lang.String[]` | `getOptions()` Gets the current settings of the Classifier.
`ASSearch` | `getSearch()` Gets the search method used
`java.lang.String` | `globalInfo()` Returns a string describing this search method
`java.lang.String` | `graph()` Returns graph describing the classifier (if possible).
`int` | `graphType()` Returns the type of graph this classifier represents.
`java.util.Enumeration` | `listOptions()` Returns an enumeration describing the available options.
`static void` | `main(java.lang.String[] argv)` Main method for testing this class.
`double` | `measureNumAttributesSelected()` Additional measure --- number of attributes selected
`double` | `measureSelectionTime()` Additional measure --- time taken (milliseconds) to select the attributes
`double` | `measureTime()` Additional measure --- time taken (milliseconds) to select attributes and build the classifier
`java.lang.String` | `searchTipText()` Returns the tip text for this property
`void` | `setEvaluator(ASEvaluation evaluator)` Sets the attribute evaluator
`void` | `setOptions(java.lang.String[] options)` Parses a given list of options.
`void` | `setSearch(ASSearch search)` Sets the search method
`java.lang.String` | `toString()` Output a representation of this classifier

Methods inherited from class weka.classifiers.SingleClassifierEnhancer
`classifierTipText, getClassifier, setClassifier`

Methods inherited from class weka.classifiers.Classifier
`classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, setDebug`

Methods inherited from class java.lang.Object
`equals, getClass, hashCode, notify, notifyAll, wait, wait, wait`

Constructor Detail

### AttributeSelectedClassifier

    public AttributeSelectedClassifier()

  Default constructor.

Method Detail

### globalInfo

    public java.lang.String globalInfo()

  Returns a string describing this search method

  Returns:
    a description of the search method suitable for displaying in the explorer/experimenter gui

### listOptions

    public java.util.Enumeration listOptions()

  Returns an enumeration describing the available options.

  Specified by:
    `listOptions` in interface `OptionHandler`
  Overrides:
    `listOptions` in class `SingleClassifierEnhancer`
  Returns:
    an enumeration of all the available options.

### setOptions

    public void setOptions(java.lang.String[] options)
                    throws java.lang.Exception

  Parses a given list of options. Valid options are:

  -W classifierstring
  Classifierstring should contain the full class name of a classifier. Any options for the classifier should appear at the end of the command line following a "--".

  -E evaluatorstring
  Evaluatorstring should contain the full class name of an attribute evaluator followed by any options. (required).

  -S searchstring
  Searchstring should contain the full class name of a search method followed by any options. (required).

  Specified by:
    `setOptions` in interface `OptionHandler`
  Overrides:
    `setOptions` in class `SingleClassifierEnhancer`
  Parameters:
    `options` - the list of options as an array of strings
  Throws:
    `java.lang.Exception` - if an option is not supported

### getOptions

    public java.lang.String[] getOptions()

  Gets the current settings of the Classifier.

  Specified by:
    `getOptions` in interface `OptionHandler`
  Overrides:
    `getOptions` in class `SingleClassifierEnhancer`
  Returns:
    an array of strings suitable for passing to setOptions

### evaluatorTipText

    public java.lang.String evaluatorTipText()

  Returns the tip text for this property

  Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui

### setEvaluator

    public void setEvaluator(ASEvaluation evaluator)

  Sets the attribute evaluator

  Parameters:
    `evaluator` - the evaluator with all options set.

### getEvaluator

    public ASEvaluation getEvaluator()

  Gets the attribute evaluator used

  Returns:
    the attribute evaluator

### searchTipText

    public java.lang.String searchTipText()

  Returns the tip text for this property

  Returns:
    tip text for this property suitable for displaying in the explorer/experimenter gui

### setSearch

    public void setSearch(ASSearch search)

  Sets the search method

  Parameters:
    `search` - the search method with all options set.

### getSearch

    public ASSearch getSearch()

  Gets the search method used

  Returns:
    the search method

### buildClassifier

    public void buildClassifier(Instances data)
                         throws java.lang.Exception

  Build the classifier on the dimensionally reduced data.

  Specified by:
    `buildClassifier` in class `Classifier`
  Parameters:
    `data` - the training data
  Throws:
    `java.lang.Exception` - if the classifier could not be built successfully

### distributionForInstance

    public double[] distributionForInstance(Instance instance)
                                     throws java.lang.Exception

  Classifies a given instance after attribute selection

  Overrides:
    `distributionForInstance` in class `Classifier`
  Parameters:
    `instance` - the instance to be classified
  Returns:
    an array containing the estimated membership probabilities of the test instance in each class or the numeric prediction
  Throws:
    `java.lang.Exception` - if instance could not be classified successfully

### graphType

    public int graphType()

  Returns the type of graph this classifier represents.

  Specified by:
    `graphType` in interface `Drawable`
  Returns:
    the type of graph representing the object

### graph

    public java.lang.String graph()
                           throws java.lang.Exception

  Returns graph describing the classifier (if possible).

  Specified by:
    `graph` in interface `Drawable`
  Returns:
    the graph of the classifier in dotty format
  Throws:
    `java.lang.Exception` - if the classifier cannot be graphed

### toString

    public java.lang.String toString()

  Output a representation of this classifier

  Overrides:
    `toString` in class `java.lang.Object`

### measureNumAttributesSelected

    public double measureNumAttributesSelected()

  Additional measure --- number of attributes selected

  Returns:
    the number of attributes selected

### measureSelectionTime

    public double measureSelectionTime()

  Additional measure --- time taken (milliseconds) to select the attributes

  Returns:
    the time taken to select attributes

### measureTime

    public double measureTime()

  Additional measure --- time taken (milliseconds) to select attributes and build the classifier

  Returns:
    the total time (select attributes + build classifier)

### enumerateMeasures

    public java.util.Enumeration enumerateMeasures()

  Returns an enumeration of the additional measure names

  Specified by:
    `enumerateMeasures` in interface `AdditionalMeasureProducer`
  Returns:
    an enumeration of the measure names

### getMeasure

    public double getMeasure(java.lang.String additionalMeasureName)

  Returns the value of the named measure

  Specified by:
    `getMeasure` in interface `AdditionalMeasureProducer`
  Parameters:
    `measureName` - the name of the measure to query for its value
  Returns:
    the value of the named measure
  Throws:
    `java.lang.IllegalArgumentException` - if the named measure is not supported

### main

    public static void main(java.lang.String[] argv)

  Main method for testing this class.

  Parameters:
    `argv` - should contain the following arguments: -t training file [-T test file] [-c class index]

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