weka.classifiers.trees
Class Id3

java.lang.Object
  weka.classifiers.Classifier
      weka.classifiers.trees.Id3

All Implemented Interfaces:

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

public class Id3

extends Classifier

Class implementing an Id3 decision tree classifier. For more information, see

R. Quinlan (1986). Induction of decision trees. Machine Learning. Vol.1, No.1, pp. 81-106.

Version:

$Revision: 1.13 $

Author:

Eibe Frank (eibe@cs.waikato.ac.nz)

See Also:

Serialized Form

Constructor Summary

Id3()

Method Summary

void	buildClassifier(Instances data) Builds Id3 decision tree classifier.
double	classifyInstance(Instance instance) Classifies a given test instance using the decision tree.
double[]	distributionForInstance(Instance instance) Computes class distribution for instance using decision tree.
java.lang.String	globalInfo() Returns a string describing the classifier.
static void	main(java.lang.String[] args) Main method.
java.lang.String	toString() Prints the decision tree using the private toString method from below.

Methods inherited from class weka.classifiers.Classifier

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

Id3

public Id3()

Method Detail

globalInfo

public java.lang.String globalInfo()

Returns a string describing the classifier.

Returns:

a description suitable for the GUI.

buildClassifier

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

Builds Id3 decision tree classifier.

Specified by:

buildClassifier in class Classifier

Parameters:

data - the training data

Throws:

java.lang.Exception - if classifier can't be built successfully

classifyInstance

public double classifyInstance(Instance instance)
                        throws NoSupportForMissingValuesException

Classifies a given test instance using the decision tree.

Overrides:

classifyInstance in class Classifier

Parameters:

instance - the instance to be classified

Returns:

the classification

Throws:

NoSupportForMissingValuesException

distributionForInstance

public double[] distributionForInstance(Instance instance)
                                 throws NoSupportForMissingValuesException

Computes class distribution for instance using decision tree.

Overrides:

distributionForInstance in class Classifier

Parameters:

instance - the instance for which distribution is to be computed

Returns:

the class distribution for the given instance

Throws:

NoSupportForMissingValuesException

toString

public java.lang.String toString()

Prints the decision tree using the private toString method from below.

Returns:

a textual description of the classifier

main

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

Main method.

Parameters:

args - the options for the classifier