weka.classifiers.bayes
Class WAODE

java.lang.Object
  weka.classifiers.Classifier
      weka.classifiers.bayes.WAODE

All Implemented Interfaces:

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

public class WAODE
extends Classifier
implements TechnicalInformationHandler

WAODE contructs the model called Weightily Averaged One-Dependence Estimators.

For more information, see

L. Jiang, H. Zhang: Weightily Averaged One-Dependence Estimators. In: Proceedings of the 9th Biennial Pacific Rim International Conference on Artificial Intelligence, PRICAI 2006, 970-974, 2006.

BibTeX:

 @inproceedings{Jiang2006,
    author = {L. Jiang and H. Zhang},
    booktitle = {Proceedings of the 9th Biennial Pacific Rim International Conference on Artificial Intelligence, PRICAI 2006},
    pages = {970-974},
    series = {LNAI},
    title = {Weightily Averaged One-Dependence Estimators},
    volume = {4099},
    year = {2006}
 }
 

Valid options are:

 -D
  If set, classifier is run in debug mode and
  may output additional info to the console

 -I
  Whether to print some more internals.
  (default: no)

Version:

$Revision: 1.2 $

Author:

Liangxiao Jiang (ljiang@cug.edu.cn), H. Zhang (hzhang@unb.ca)

See Also:

Serialized Form

Constructor Summary

WAODE()

Method Summary

void	buildClassifier(Instances instances) Generates the classifier.
double[]	distributionForInstance(Instance instance) Calculates the class membership probabilities for the given test instance
er, int)">makeCoODE>

Methods inherited from interface weka.classifiers.UpdateableClassifier

updateClassifier

Constructor Detail

NaiveBayesUpdateable

public NaiveBayesUpdateable()

Method Detail

globalInfo

public java.lang.String globalInfo()

Returns a string describing this classifier

Overrides:

globalInfo in class NaiveBayes

Returns:

a description of the classifier suitable for displaying in the explorer/experimenter gui

getTechnicalInformation

public TechnicalInformation getTechnicalInformation()

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

Specified by:

getTechnicalInformation in interface TechnicalInformationHandler

Overrides:

getTechnicalInformation in class NaiveBayes

Returns:

the technical information about this class

setUseSupervisedDiscretization

public void setUseSupervisedDiscretization(boolean newblah)

Set whether supervised discretization is to be used.

Overrides:

setUseSupervisedDiscretization in class NaiveBayes

Parameters:

newblah - true if supervised discretization is to be used.

main

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

Main method for testing this class.

Parameters:

argv - the options