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java.lang.Objectweka.classifiers.Classifier
weka.classifiers.rules.PART
public class PART
Class for generating a PART decision list. For more information, see
Eibe Frank and Ian H. Witten (1998). Generating Accurate Rule Sets Without Global Optimization. In Shavlik, J., ed., Machine Learning: Proceedings of the Fifteenth International Conference, Morgan Kaufmann Publishers, San Francisco, CA.
Valid options are:
-C confidence
Set confidence threshold for pruning. (Default: 0.25)
-M number
Set minimum number of instances per leaf. (Default: 2)
-R
Use reduced error pruning.
-N number
Set number of folds for reduced error pruning. One fold is
used as the pruning set. (Default: 3)
-B
Use binary splits for nominal attributes.
-U
Generate unpruned decision list.
-Q
The seed for reduced-error pruning.
| Constructor Summary | |
|---|---|
PART()
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|
| Method Summary | |
|---|---|
java.lang.String |
binarySplitsTipText()
Returns the tip text for this property |
void |
buildClassifier(Instances instances)
Generates the classifier. |
double |
classifyInstance(Instance instance)
Classifies an instance. |
java.lang.String |
confidenceFactorTipText()
Returns the tip text for this property |
double[] |
distributionForInstance(Instance instance)
Returns class probabilities for an instance. |
java.util.Enumeration |
enumerateMeasures()
Returns an enumeration of the additional measure names |
boolean |
getBinarySplits()
Get the value of binarySplits. |
float |
getConfidenceFactor()
Get the value of CF. |
double |
getMeasure(java.lang.String additionalMeasureName)
Returns the value of the named measure |
int |
getMinNumObj()
Get the value of minNumObj. |
int |
getNumFolds()
Get the value of numFolds. |
java.lang.String[] |
getOptions()
Gets the current settings of the Classifier. |
boolean |
getReducedErrorPruning()
Get the value of reducedErrorPruning. |
int |
getSeed()
Get the value of Seed. |
boolean |
getUnpruned()
Get the value of unpruned. |
java.lang.String |
globalInfo()
Returns a string describing classifier |
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 |
measureNumRules()
Return the number of rules. |
java.lang.String |
minNumObjTipText()
Returns the tip text for this property |
java.lang.String |
numFoldsTipText()
Returns the tip text for this property |
java.lang.String |
reducedErrorPruningTipText()
Returns the tip text for this property |
java.lang.String |
seedTipText()
Returns the tip text for this property |
void |
setBinarySplits(boolean v)
Set the value of binarySplits. |
void |
setConfidenceFactor(float v)
Set the value of CF. |
void |
setMinNumObj(int v)
Set the value of minNumObj. |
void |
setNumFolds(int v)
Set the value of numFolds. |
void |
setOptions(java.lang.String[] options)
Parses a given list of options. |
void |
setReducedErrorPruning(boolean v)
Set the value of reducedErrorPruning. |
void |
setSeed(int newSeed)
Set the value of Seed. |
void |
setUnpruned(boolean newunpruned)
Set the value of unpruned. |
java.lang.String |
toString()
Returns a description of the classifier |
java.lang.String |
toSummaryString()
Returns a superconcise version of the model |
java.lang.String |
unprunedTipText()
Returns the tip text for this property |
| Methods inherited from class weka.classifiers.Classifier |
|---|
debugTipText, forName, getDebug, makeCopies, makeCopy, setDebug |
| Methods inherited from class java.lang.Object |
|---|
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait |
| Constructor Detail |
|---|
public PART()
| Method Detail |
|---|
public java.lang.String globalInfo()
public void buildClassifier(Instances instances)
throws java.lang.Exception
buildClassifier in class Classifierinstances - set of instances serving as training data
java.lang.Exception - if classifier can't be built successfully
public double classifyInstance(Instance instance)
throws java.lang.Exception
classifyInstance in class Classifierinstance - the instance to be classified
java.lang.Exception - if instance can't be classified successfully
public final double[] distributionForInstance(Instance instance)
throws java.lang.Exception
distributionForInstance in class Classifierinstance - the instance to be classified
java.lang.Exception - if the distribution can't be computed successfullypublic java.util.Enumeration listOptions()
-C confidence
Set confidence threshold for pruning. (Default: 0.25)
-M number
Set minimum number of instances per leaf. (Default: 2)
-R
Use reduced error pruning.
-N number
Set number of folds for reduced error pruning. One fold is
used as the pruning set. (Default: 3)
-B
Use binary splits for nominal attributes.
-U
Generate unpruned decision list.
-Q
The seed for reduced-error pruning.
listOptions in interface OptionHandlerlistOptions in class Classifier
public void setOptions(java.lang.String[] options)
throws java.lang.Exception
setOptions in interface OptionHandlersetOptions in class Classifieroptions - the list of options as an array of strings
java.lang.Exception - if an option is not supportedpublic java.lang.String[] getOptions()
getOptions in interface OptionHandlergetOptions in class Classifierpublic java.lang.String toString()
toString in class java.lang.Objectpublic java.lang.String toSummaryString()
toSummaryString in interface Summarizablepublic double measureNumRules()
public java.util.Enumeration enumerateMeasures()
enumerateMeasures in interface AdditionalMeasureProducerpublic double getMeasure(java.lang.String additionalMeasureName)
getMeasure in interface AdditionalMeasureProducermeasureName - the name of the measure to query for its value
java.lang.IllegalArgumentException - if the named measure is not supportedpublic java.lang.String confidenceFactorTipText()
public float getConfidenceFactor()
public void setConfidenceFactor(float v)
v - Value to assign to CF.public java.lang.String minNumObjTipText()
public int getMinNumObj()
public void setMinNumObj(int v)
v - Value to assign to minNumObj.public java.lang.String reducedErrorPruningTipText()
public boolean getReducedErrorPruning()
public void setReducedErrorPruning(boolean v)
v - Value to assign to reducedErrorPruning.public java.lang.String unprunedTipText()
public boolean getUnpruned()
public void setUnpruned(boolean newunpruned)
newunpruned - Value to assign to unpruned.public java.lang.String numFoldsTipText()
public int getNumFolds()
public void setNumFolds(int v)
v - Value to assign to numFolds.public java.lang.String seedTipText()
public int getSeed()
public void setSeed(int newSeed)
newSeed - Value to assign to Seed.public java.lang.String binarySplitsTipText()
public boolean getBinarySplits()
public void setBinarySplits(boolean v)
v - Value to assign to binarySplits.public static void main(java.lang.String[] argv)
String - options
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