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Class weka.classifiers.j48.C45Split

java.lang.Object
    |
    +----weka.classifiers.j48.ClassifierSplitModel
            |
            +----weka.classifiers.j48.C45Split

public class C45Split
extends ClassifierSplitModel
Class implementing a C4.5-type split on an attribute.

Version:
$Revision: 1.6 $
Author:
Eibe Frank (eibe@cs.waikato.ac.nz)

Constructor Index

 o C45Split(int, int, double)
Initializes the split model.

Method Index

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

Constructor Detail

 o C45Split
public C45Split(int attIndex,
                int minNoObj,
                double sumOfWeights)
          Initializes the split model.

Method Detail

 o buildClassifier
public void buildClassifier(Instances trainInstances) throws java.lang.Exception
          Creates a C4.5-type split on the given data. Assumes that none of the class values is missing.
Throws:
java.lang.Exception - if something goes wrong
Overrides:
buildClassifier in class ClassifierSplitModel
 o attIndex
public final int attIndex()
          Returns index of attribute for which split was generated.
 o classProb
public final double classProb(int classIndex,
                              Instance instance,
                              int theSubset) throws java.lang.Exception
          Gets class probability for instance.
Throws:
java.lang.Exception - if something goes wrong
Overrides:
classProb in class ClassifierSplitModel
 o codingCost
public final double codingCost()
          Returns coding cost for split (used in rule learner).
Overrides:
codingCost in class ClassifierSplitModel
 o gainRatio
public final double gainRatio()
          Returns (C4.5-type) gain ratio for the generated split.
 o infoGain
public final double infoGain()
          Returns (C4.5-type) information gain for the generated split.
 o leftSide
public final java.lang.String leftSide(Instances data)
          Prints left side of condition..
Parameters:
data - training set.
Overrides:
leftSide in class ClassifierSplitModel
 o rightSide
public final java.lang.String rightSide(int index,
                              Instances data)
          Prints the condition satisfied by instances in a subset.
Parameters:
index - of subset
data - training set.
Overrides:
rightSide in class ClassifierSplitModel
 o 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".
Parameters:
index - index of the nominal value tested
data - the data containing instance structure info
Returns:
a value of type 'String'
Overrides:
sourceExpression in class ClassifierSplitModel
 o 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).
 o minsAndMaxs
public final double[][] minsAndMaxs(Instances data,
                                    double minsAndMaxs[][],
                                    int index)
          Returns the minsAndMaxs of the index.th subset.
 o resetDistribution
public void resetDistribution(Instances data) throws java.lang.Exception
          Sets distribution associated with model.
Overrides:
resetDistribution in class ClassifierSplitModel
 o 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.
Overrides:
weights in class ClassifierSplitModel
 o 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.
Throws:
java.lang.Exception - if something goes wrong
Overrides:
whichSubset in class ClassifierSplitModel

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