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Class weka.classifiers.j48.PART

java.lang.Object
    |
    +----weka.classifiers.Classifier
            |
            +----weka.classifiers.DistributionClassifier
                    |
                    +----weka.classifiers.j48.PART

public class PART
extends DistributionClassifier
implements OptionHandler, WeightedInstancesHandler, Summarizable, AdditionalMeasureProducer
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.

Version:
$Revision: 1.14 $
Author:
Eibe Frank (eibe@cs.waikato.ac.nz)

Constructor Index

 o PART()
 

Method Index

 o buildClassifier(Instances)
Generates the classifier.
 o classifyInstance(Instance)
Classifies an instance.
 o distributionForInstance(Instance)
Returns class probabilities for an instance.
 o enumerateMeasures()
Returns an enumeration of the additional measure names
 o getBinarySplits()
Get the value of binarySplits.
 o getConfidenceFactor()
Get the value of CF.
 o getMeasure(String)
Returns the value of the named measure
 o getMinNumObj()
Get the value of minNumObj.
 o getNumFolds()
Get the value of numFolds.
 o getOptions()
Gets the current settings of the Classifier.
 o getReducedErrorPruning()
Get the value of reducedErrorPruning.
 o listOptions()
Returns an enumeration describing the available options Valid options are:

-C confidence
Set confidence threshold for pruning.

 o main(String[])
Main method for testing this class.
 o measureNumRules()
Return the number of rules.
 o setBinarySplits(boolean)
Set the value of binarySplits.
 o setConfidenceFactor(float)
Set the value of CF.
 o setMinNumObj(int)
Set the value of minNumObj.
 o setNumFolds(int)
Set the value of numFolds.
 o setOptions(String[])
Parses a given list of options.
 o setReducedErrorPruning(boolean)
Set the value of reducedErrorPruning.
 o toString()
Returns a description of the classifier
 o toSummaryString()
Returns a superconcise version of the model

Constructor Detail

 o PART
public PART()

Method Detail

 o buildClassifier
public void buildClassifier(Instances instances) throws java.lang.Exception
          Generates the classifier.
Throws:
java.lang.Exception - if classifier can't be built successfully
Overrides:
buildClassifier in class Classifier
 o classifyInstance
public double classifyInstance(Instance instance) throws java.lang.Exception
          Classifies an instance.
Throws:
java.lang.Exception - if instance can't be classified successfully
Overrides:
classifyInstance in class DistributionClassifier
 o distributionForInstance
public final double[] distributionForInstance(Instance instance) throws java.lang.Exception
          Returns class probabilities for an instance.
Throws:
java.lang.Exception - if the distribution can't be computed successfully
Overrides:
distributionForInstance in class DistributionClassifier
 o listOptions
public java.util.Enumeration listOptions()
          Returns an enumeration describing the available options 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.

Returns:
an enumeration of all the available options
 o setOptions
public void setOptions(java.lang.String options[]) throws java.lang.Exception
          Parses a given list of options.
Parameters:
options - the list of options as an array of strings
Throws:
java.lang.Exception - if an option is not supported
 o getOptions
public java.lang.String[] getOptions()
          Gets the current settings of the Classifier.
Returns:
an array of strings suitable for passing to setOptions
 o toString
public java.lang.String toString()
          Returns a description of the classifier
Overrides:
toString in class java.lang.Object
 o toSummaryString
public java.lang.String toSummaryString()
          Returns a superconcise version of the model
 o measureNumRules
public double measureNumRules()
          Return the number of rules.
Returns:
the number of rules
 o enumerateMeasures
public java.util.Enumeration enumerateMeasures()
          Returns an enumeration of the additional measure names
Returns:
an enumeration of the measure names
 o getMeasure
public double getMeasure(java.lang.String additionalMeasureName)
          Returns the value of the named measure
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
 o getConfidenceFactor
public float getConfidenceFactor()
          Get the value of CF.
Returns:
Value of CF.
 o setConfidenceFactor
public void setConfidenceFactor(float v)
          Set the value of CF.
Parameters:
v - Value to assign to CF.
 o getMinNumObj
public int getMinNumObj()
          Get the value of minNumObj.
Returns:
Value of minNumObj.
 o setMinNumObj
public void setMinNumObj(int v)
          Set the value of minNumObj.
Parameters:
v - Value to assign to minNumObj.
 o getReducedErrorPruning
public boolean getReducedErrorPruning()
          Get the value of reducedErrorPruning.
Returns:
Value of reducedErrorPruning.
 o setReducedErrorPruning
public void setReducedErrorPruning(boolean v)
          Set the value of reducedErrorPruning.
Parameters:
v - Value to assign to reducedErrorPruning.
 o getNumFolds
public int getNumFolds()
          Get the value of numFolds.
Returns:
Value of numFolds.
 o setNumFolds
public void setNumFolds(int v)
          Set the value of numFolds.
Parameters:
v - Value to assign to numFolds.
 o getBinarySplits
public boolean getBinarySplits()
          Get the value of binarySplits.
Returns:
Value of binarySplits.
 o setBinarySplits
public void setBinarySplits(boolean v)
          Set the value of binarySplits.
Parameters:
v - Value to assign to binarySplits.
 o main
public static void main(java.lang.String argv[])
          Main method for testing this class.
Parameters:
String - options

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