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## weka.classifiers.trees
Class DecisionStump

    java.lang.Object
      weka.classifiers.Classifier
          weka.classifiers.trees.DecisionStump

All Implemented Interfaces:
  java.io.Serializable, java.lang.Cloneable, Sourcable, OptionHandler, WeightedInstancesHandler

    public class DecisionStump

extends Classifier
implements WeightedInstancesHandler, Sourcable

Class for building and using a decision stump. Usually used in conjunction with a boosting algorithm. Typical usage:

`java weka.classifiers.trees.LogitBoost -I 100 -W weka.classifiers.trees.DecisionStump -t training_data`

Version:
  $Revision: 1.18.2.1 $
Author:
  Eibe Frank (eibe@cs.waikato.ac.nz)
See Also:
  Serialized Form

Constructor Summary
`DecisionStump()`

Method Summary
`void` | `buildClassifier(Instances instances)` Generates the classifier.
`double[]` | `distributionForInstance(Instance instance)` Calculates the class membership probabilities for the given test instance.
`java.lang.String` | `globalInfo()` Returns a string describing classifier
`static void` | `main(java.lang.String[] argv)` Main method for testing this class.
`java.lang.String` | `toSource(java.lang.String className)` Returns the decision tree as Java source code.
`java.lang.String` | `toString()` Returns a description of the classifier.

Methods inherited from class weka.classifiers.Classifier
`classifyInstance, debugTipText, forName, getDebug, getOptions, listOptions, makeCopies, makeCopy, setDebug, setOptions`

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

Constructor Detail

### DecisionStump

    public DecisionStump()

Method Detail

### globalInfo

    public java.lang.String globalInfo()

  Returns a string describing classifier

  Returns:
    a description suitable for displaying in the explorer/experimenter gui

### buildClassifier

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

  Generates the classifier.

  Specified by:
    `buildClassifier` in class `Classifier`
  Parameters:
    `instances` - set of instances serving as training data
  Throws:
    `java.lang.Exception` - if the classifier has not been generated successfully

### distributionForInstance

    public double[] distributionForInstance(Instance instance)
                                     throws java.lang.Exception

  Calculates the class membership probabilities for the given test instance.

  Overrides:
    `distributionForInstance` in class `Classifier`
  Parameters:
    `instance` - the instance to be classified
  Returns:
    predicted class probability distribution
  Throws:
    `java.lang.Exception` - if distribution can't be computed

### toSource

    public java.lang.String toSource(java.lang.String className)
                              throws java.lang.Exception

  Returns the decision tree as Java source code.

  Specified by:
    `toSource` in interface `Sourcable`
  Parameters:
    `className` - the name that should be given to the source class.
  Returns:
    the tree as Java source code
  Throws:
    `java.lang.Exception` - if something goes wrong

### toString

    public java.lang.String toString()

  Returns a description of the classifier.

  Overrides:
    `toString` in class `java.lang.Object`
  Returns:
    a description of the classifier as a string.

### main

    public static void main(java.lang.String[] argv)

  Main method for testing this class.

  Parameters:
    `argv` - the options

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