weka.classifiers.trees
Class DecisionStump

java.lang.Object
  |
  +--weka.classifiers.Classifier
        |
        +--weka.classifiers.trees.DecisionStump

All Implemented Interfaces:

java.lang.Cloneable, OptionHandler, java.io.Serializable, Sourcable, 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 $

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, 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