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## weka.classifiers.lazy.kstar
Class KStarNominalAttribute

    java.lang.Object
      weka.classifiers.lazy.kstar.KStarNominalAttribute

All Implemented Interfaces:
  KStarConstants, RevisionHandler

    public class KStarNominalAttribute

extends java.lang.Object
implements KStarConstants, RevisionHandler

A custom class which provides the environment for computing the transformation probability of a specified test instance nominal attribute to a specified train instance nominal attribute.

Version:
  $Revision 1.0 $
Author:
  Len Trigg (len@reeltwo.com), Abdelaziz Mahoui (am14@cs.waikato.ac.nz)

Field Summary

Fields inherited from interface weka.classifiers.lazy.kstar.KStarConstants
`B_ENTROPY, B_SPHERE, EPSILON, FLOOR, FLOOR1, INITIAL_STEP, LOG2, M_AVERAGE, M_DELETE, M_MAXDIFF, M_NORMAL, NUM_RAND_COLS, OFF, ON, ROOT_FINDER_ACCURACY, ROOT_FINDER_MAX_ITER`

Constructor Summary
`KStarNominalAttribute(Instance test, Instance train, int attrIndex, Instances trainSet, int[][] randClassCol, KStarCache cache)` Constructor

Method Summary
`java.lang.String` | `getRevision()` Returns the revision string.
`void` | `setOptions(int missingmode, int blendmethod, int blendfactor)` Sets the options.
`double` | `transProb()` Calculates the probability of the indexed nominal attribute of the test instance transforming into the indexed nominal attribute of the training instance.

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

Constructor Detail

### KStarNominalAttribute

    public KStarNominalAttribute(Instance test,
                                 Instance train,
                                 int attrIndex,
                                 Instances trainSet,
                                 int[][] randClassCol,
                                 KStarCache cache)

  Constructor

Method Detail

### transProb

    public double transProb()

  Calculates the probability of the indexed nominal attribute of the test instance transforming into the indexed nominal attribute of the training instance.

  Returns:
    the value of the transformation probability.

### setOptions

    public void setOptions(int missingmode,
                           int blendmethod,
                           int blendfactor)

  Sets the options.

### getRevision

    public java.lang.String getRevision()

  Returns the revision string.

  Specified by:
    `getRevision` in interface `RevisionHandler`
  Returns:
    the revision

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