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## weka.classifiers.trees.j48
Class ClassifierSplitModel

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

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

Direct Known Subclasses:
  BinC45Split, C45Split, NBTreeNoSplit, NBTreeSplit, NoSplit, ResidualSplit

    public abstract class ClassifierSplitModel

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

Abstract class for classification models that can be used recursively to split the data.

Version:
  $Revision: 1.8 $
Author:
  Eibe Frank (eibe@cs.waikato.ac.nz)
See Also:
  Serialized Form

Constructor Summary
`ClassifierSplitModel()`

Method Summary
`abstract void` | `buildClassifier(Instances instances)` Builds the classifier split model for the given set of instances.
`boolean` | `checkModel()` Checks if generated model is valid.
`double` | `classifyInstance(Instance instance)` Classifies a given instance.
`double` | `classProb(int classIndex, Instance instance, int theSubset)` Gets class probability for instance.
`double` | `classProbLaplace(int classIndex, Instance instance, int theSubset)` Gets class probability for instance.
`java.lang.Object` | `clone()` Allows to clone a model (shallow copy).
`double` | `codingCost()` Returns coding costs of model.
`Distribution` | `distribution()` Returns the distribution of class values induced by the model.
`java.lang.String` | `dumpLabel(int index, Instances data)` Prints label for subset index of instances (eg class).
`java.lang.String` | `dumpModel(Instances data)` Prints the split model.
`abstract java.lang.String` | `leftSide(Instances data)` Prints left side of condition satisfied by instances.
`int` | `numSubsets()` Returns the number of created subsets for the split.
`void` | `resetDistribution(Instances data)` Sets distribution associated with model.
`abstract java.lang.String` | `rightSide(int index, Instances data)` Prints left side of condition satisfied by instances in subset index.
`java.lang.String` | `sourceClass(int index, Instances data)`
`abstract java.lang.String` | `sourceExpression(int index, Instances data)`
`Instances[]` | `split(Instances data)` Splits the given set of instances into subsets.
`abstract double[]` | `weights(Instance instance)` Returns weights if instance is assigned to more than one subset.
`abstract int` | `whichSubset(Instance instance)` Returns index of subset instance is assigned to.

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

Constructor Detail

### ClassifierSplitModel

    public ClassifierSplitModel()

Method Detail

### clone

    public java.lang.Object clone()

  Allows to clone a model (shallow copy).

  Overrides:
    `clone` in class `java.lang.Object`

### buildClassifier

    public abstract void buildClassifier(Instances instances)
                                  throws java.lang.Exception

  Builds the classifier split model for the given set of instances.

  Throws:
    `java.lang.Exception` - if something goes wrong

### checkModel

    public final boolean checkModel()

  Checks if generated model is valid.

### classifyInstance

    public final double classifyInstance(Instance instance)
                                  throws java.lang.Exception

  Classifies a given instance.

  Throws:
    `java.lang.Exception` - if something goes wrong

### classProb

    public 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

### classProbLaplace

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

  Gets class probability for instance.

  Throws:
    `java.lang.Exception` - if something goes wrong

### codingCost

    public double codingCost()

  Returns coding costs of model. Returns 0 if not overwritten.

### distribution

    public final Distribution distribution()

  Returns the distribution of class values induced by the model.

### leftSide

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

  Prints left side of condition satisfied by instances.

  Parameters:
    `data` - the data.

### rightSide

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

  Prints left side of condition satisfied by instances in subset index.

### dumpLabel

    public final java.lang.String dumpLabel(int index,
                                            Instances data)
                                     throws java.lang.Exception

  Prints label for subset index of instances (eg class).

  Throws:
    `java.lang.Exception` - if something goes wrong

### sourceClass

    public final java.lang.String sourceClass(int index,
                                              Instances data)
                                       throws java.lang.Exception

  Throws:
    `java.lang.Exception`

### sourceExpression

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

### dumpModel

    public final java.lang.String dumpModel(Instances data)
                                     throws java.lang.Exception

  Prints the split model.

  Throws:
    `java.lang.Exception` - if something goes wrong

### numSubsets

    public final int numSubsets()

  Returns the number of created subsets for the split.

### resetDistribution

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

  Sets distribution associated with model.

  Throws:
    `java.lang.Exception`

### split

    public final Instances[] split(Instances data)
                            throws java.lang.Exception

  Splits the given set of instances into subsets.

  Throws:
    `java.lang.Exception` - if something goes wrong

### weights

    public abstract 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.

### whichSubset

    public abstract 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

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