weka.classifiers.trees.j48
Class BinC45Split

java.lang.Object
  weka.classifiers.trees.j48.ClassifierSplitModel
      weka.classifiers.trees.j48.BinC45Split

All Implemented Interfaces:

java.lang.Cloneable, java.io.Serializable

public class BinC45Split

extends ClassifierSplitModel

Class implementing a binary C4.5-like split on an attribute.

Version:

$Revision: 1.9 $

Author:

Eibe Frank (eibe@cs.waikato.ac.nz)

See Also:

Serialized Form

Constructor Summary

BinC45Split(int attIndex, int minNoObj, double sumOfWeights)
Initializes the split model.

Method Summary

int	attIndex() Returns index of attribute for which split was generated.
void	buildClassifier(Instances trainInstances) Creates a C4.5-type split on the given data.
double	classProb(int classIndex, Instance instance, int theSubset) Gets class probability for instance.
double	gainRatio() Returns (C4.5-type) gain ratio for the generated split.
double	infoGain() Returns (C4.5-type) information gain for the generated split.
java.lang.String	leftSide(Instances data) Prints left side of condition..
void	resetDistribution(Instances data) Sets distribution associated with model.
java.lang.String	rightSide(int index, Instances data) Prints the condition satisfied by instances in a subset.
void	setSplitPoint(Instances allInstances) Sets split point to greatest value in given data smaller or equal to old split point.
java.lang.String	sourceExpression(int index, Instances data) Returns a string containing java source code equivalent to the test made at this node.
double[]	weights(Instance instance) Returns weights if instance is assigned to more than one subset.
int	whichSubset(Instance instance) Returns index of subset instance is assigned to.

Methods inherited from class weka.classifiers.trees.j48.ClassifierSplitModel

checkModel, classifyInstance, classProbLaplace, clone, codingCost, distribution, dumpLabel, dumpModel, numSubsets, sourceClass, split

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

BinC45Split

public BinC45Split(int attIndex,
                   int minNoObj,
                   double sumOfWeights)

Initializes the split model.

Method Detail

buildClassifier

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

Creates a C4.5-type split on the given data.

Specified by:

buildClassifier in class ClassifierSplitModel

Throws:

java.lang.Exception - if something goes wrong

attIndex

public final int attIndex()

Returns index of attribute for which split was generated.

gainRatio

public final double gainRatio()

Returns (C4.5-type) gain ratio for the generated split.

classProb

public final double classProb(int classIndex,
                              Instance instance,
                              int theSubset)
                       throws java.lang.Exception

Gets class probability for instance.

Overrides:

classProb in class ClassifierSplitModel

Throws:

java.lang.Exception - if something goes wrong

infoGain

public final double infoGain()

Returns (C4.5-type) information gain for the generated split.

leftSide

public final java.lang.String leftSide(Instances data)

Prints left side of condition..

Specified by:

leftSide in class ClassifierSplitModel

Parameters:

data - the data.

rightSide

public final java.lang.String rightSide(int index,
                                        Instances data)

Prints the condition satisfied by instances in a subset.

Specified by:

rightSide in class ClassifierSplitModel

Parameters:

index - of subset and training set.

sourceExpression

public final java.lang.String sourceExpression(int index,
                                               Instances data)

Returns a string containing java source code equivalent to the test made at this node. The instance being tested is called "i".

Specified by:

sourceExpression in class ClassifierSplitModel

Parameters:

index - index of the nominal value tested

data - the data containing instance structure info

Returns:

a value of type 'String'

setSplitPoint

public final void setSplitPoint(Instances allInstances)

Sets split point to greatest value in given data smaller or equal to old split point. (C4.5 does this for some strange reason).

resetDistribution

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

Sets distribution associated with model.

Overrides:

resetDistribution in class ClassifierSplitModel

Throws:

java.lang.Exception

weights

public final double[] weights(Instance instance)

Returns weights if instance is assigned to more than one subset. Returns null if instance is only assigned to one subset.

Specified by:

weights in class ClassifierSplitModel

whichSubset

public final int whichSubset(Instance instance)
                      throws java.lang.Exception

Returns index of subset instance is assigned to. Returns -1 if instance is assigned to more than one subset.

Specified by:

whichSubset in class ClassifierSplitModel

Throws:

java.lang.Exception - if something goes wrong