net.sf.bddbddb.order
Class MyId3

java.lang.Object
  weka.classifiers.Classifier
      net.sf.bddbddb.order.MyId3

All Implemented Interfaces:

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

public class MyId3
extends weka.classifiers.Classifier

Class implementing an Id3 decision tree classifier. This version differs from the weka one in that it supports missing attributes.

Version:

$Revision: 531 $

Author:

Eibe Frank (eibe@cs.waikato.ac.nz), John Whaley

See Also:

Serialized Form

Field Summary

Fields inherited from class weka.classifiers.Classifier

m_Debug

Constructor Summary

MyId3()

Method Summary

void	buildClassifier(weka.core.Instances data) Builds Id3 decision tree classifier.
double	classifyInstance(weka.core.Instance instance) Classifies a given test instance using the decision tree.
double[]	distributionForInstance(weka.core.Instance instance) Computes class distribution for instance using decision tree.
boolean	getAttribCombos(weka.core.Instances i, double cv)
java.util.List	getAttribCombos(int nAttribs, double cv)
java.lang.String	globalInfo() Returns a string describing the classifier.
void	laplaceSmooth(double[] dist, double sum, int numClasses)
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

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

MyId3

public MyId3()

Method Detail

getAttribCombos

public boolean getAttribCombos(weka.core.Instances i,
                               double cv)

getAttribCombos

public java.util.List getAttribCombos(int nAttribs,
                                      double cv)

globalInfo

public java.lang.String globalInfo()

Returns a string describing the classifier.

Returns:

a description suitable for the GUI.

buildClassifier

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

Builds Id3 decision tree classifier.

Specified by:

buildClassifier in class weka.classifiers.Classifier

Parameters:

data - the training data

Throws:

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

laplaceSmooth

public void laplaceSmooth(double[] dist,
                          double sum,
                          int numClasses)

classifyInstance

public double classifyInstance(weka.core.Instance instance)

Classifies a given test instance using the decision tree.

Overrides:

classifyInstance in class weka.classifiers.Classifier

Parameters:

instance - the instance to be classified

Returns:

the classification

distributionForInstance

public double[] distributionForInstance(weka.core.Instance instance)
                                 throws weka.core.NoSupportForMissingValuesException

Computes class distribution for instance using decision tree.

Overrides:

distributionForInstance in class weka.classifiers.Classifier

Parameters:

instance - the instance for which distribution is to be computed

Returns:

the class distribution for the given instance

Throws:

weka.core.NoSupportForMissingValuesException

toString

public java.lang.String toString()

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

Overrides:

toString in class java.lang.Object

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