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## weka.classifiers.trees.j48
Class BinC45Split

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

All Implemented Interfaces:
  java.io.Serializable, java.lang.Cloneable, RevisionHandler

    public class BinC45Split

extends ClassifierSplitModel

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

Version:
  $Revision: 6073 $
Author:
  Eibe Frank (eibe@cs.waikato.ac.nz)
See Also:
  Serialized Form

Constructor Summary
`BinC45Split(int attIndex, int minNoObj, double sumOfWeights, boolean useMDLcorrection)` 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.
`java.lang.String` | `getRevision()` Returns the revision string.
`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` | `splitPoint()` Returns the split point (numeric attribute only).
`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,
                       boolean useMDLcorrection)

  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.

### splitPoint

    public double splitPoint()

  Returns the split point (numeric attribute only).

  Returns:
    the split point used for a test on a numeric attribute

### 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 to get the attribute name from.
  Returns:
    the attribute name

### 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

### getRevision

    public java.lang.String getRevision()

  Returns the revision string.

  Returns:
    the revision

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