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: 10531 $
  Author:
    Eibe Frank (eibe@cs.waikato.ac.nz)
  See Also:
    Serialized Form

- - ### Constructor Summary

    Constructors
    Constructor and Description
    `BinC45Split(int attIndex, int minNoObj, double sumOfWeights, boolean useMDLcorrection)` Initializes the split model.

  - ### Method Summary

    Methods
    Modifier and Type | Method and Description
    --- | ---
    `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