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## weka.classifiers.trees.j48
Class SplitCriterion

    java.lang.Object
      weka.classifiers.trees.j48.SplitCriterion

All Implemented Interfaces:
  java.io.Serializable

Direct Known Subclasses:
  EntropyBasedSplitCrit

    public abstract class SplitCriterion

extends java.lang.Object
implements java.io.Serializable

Abstract class for computing splitting criteria with respect to distributions of class values.

Version:
  $Revision: 1.5 $
Author:
  Eibe Frank (eibe@cs.waikato.ac.nz)
See Also:
  Serialized Form

Constructor Summary
`SplitCriterion()`

Method Summary
`double` | `splitCritValue(Distribution bags)` Computes result of splitting criterion for given distribution.
`double` | `splitCritValue(Distribution train, Distribution test)` Computes result of splitting criterion for given training and test distributions.
`double` | `splitCritValue(Distribution train, Distribution test, Distribution defC)` Computes result of splitting criterion for given training and test distributions and given default distribution.
`double` | `splitCritValue(Distribution train, Distribution test, int noClassesDefault)` Computes result of splitting criterion for given training and test distributions and given number of classes.

Methods inherited from class java.lang.Object
`equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

Constructor Detail

### SplitCriterion

    public SplitCriterion()

Method Detail

### splitCritValue

    public double splitCritValue(Distribution bags)

  Computes result of splitting criterion for given distribution.

  Returns:
    value of splitting criterion. 0 by default

### splitCritValue

    public double splitCritValue(Distribution train,
                                 Distribution test)

  Computes result of splitting criterion for given training and test distributions.

  Returns:
    value of splitting criterion. 0 by default

### splitCritValue

    public double splitCritValue(Distribution train,
                                 Distribution test,
                                 int noClassesDefault)

  Computes result of splitting criterion for given training and test distributions and given number of classes.

  Returns:
    value of splitting criterion. 0 by default

### splitCritValue

    public double splitCritValue(Distribution train,
                                 Distribution test,
                                 Distribution defC)

  Computes result of splitting criterion for given training and test distributions and given default distribution.

  Returns:
    value of splitting criterion. 0 by default

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