weka.classifiers.bayes
Class BayesNetB

java.lang.Object
  weka.classifiers.Classifier
      weka.classifiers.bayes.BayesNet
          weka.classifiers.bayes.BayesNetB

All Implemented Interfaces:

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

Direct Known Subclasses:

BayesNetB2

public class BayesNetB

extends BayesNet

Class for a Bayes Network classifier based on a hill climbing algorithm for learning structure as described in Buntine, W. (1991). Theory refinement on Bayesian networks. In Proceedings of Seventh Conference on Uncertainty in Artificial Intelligence, Los Angeles, CA, pages 52--60. Morgan Kaufmann. Works with nominal variables and no missing values only.

Version:

$Revision: 1.3 $

Author:

Remco Bouckaert (rrb@xm.co.nz)

See Also:

Serialized Form

Field Summary

Fields inherited from class weka.classifiers.bayes.BayesNet

m_ADTree, m_bInitAsNaiveBayes, m_bUseADTree, m_Distributions, m_fAlpha, m_Instances, m_nMaxNrOfParents, m_nOrder, m_nScoreType, m_NumClasses, m_ParentSets, TAGS_SCORE_TYPE

Fields inherited from class weka.classifiers.Classifier

m_Debug

Fields inherited from interface weka.core.Drawable

BayesNet, NOT_DRAWABLE, TREE

Constructor Summary

BayesNetB()

Method Summary

private boolean	AddArcMakesSense(int iAttributeHead, int iAttributeTail) AddArcMakesSense checks whether adding the arc from iAttributeTail to iAttributeHead does not already exists and does not introduce a cycle
void	buildStructure() buildStructure determines the network structure/graph of the network with Buntines greedy hill climbing algorithm, restricted by its initial structure (which can be an empty graph, or a Naive Bayes graph.
java.lang.String	globalInfo() This will return a string describing the classifier.
static void	main(java.lang.String[] argv) Main method for testing this class.

Methods inherited from class weka.classifiers.bayes.BayesNet

alphaTipText, buildClassifier, CalcNodeScore, CalcScoreOfCounts, CalcScoreOfCounts2, CalcScoreWithExtraParent, countsForInstance, distributionForInstance, estimateCPTs, getAlpha, getInitAsNaiveBayes, getMaxNrOfParents, getOptions, getScoreType, getUseADTree, graph, graphType, initAsNaiveBayesTipText, initStructure, listOptions, logScore, maxNrOfParentsTipText, scoreTypeTipText, setAlpha, setInitAsNaiveBayes, setMaxNrOfParents, setOptions, setScoreType, setUseADTree, toString, toXMLBIF03, updateClassifier, useADTreeTipText, XMLNormalize

Methods inherited from class weka.classifiers.Classifier

classifyInstance, debugTipText, forName, getDebug, makeCopies, setDebug

Methods inherited from class java.lang.Object

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

Constructor Detail

BayesNetB

public BayesNetB()

Method Detail

buildStructure

public void buildStructure()
                    throws java.lang.Exception

buildStructure determines the network structure/graph of the network with Buntines greedy hill climbing algorithm, restricted by its initial structure (which can be an empty graph, or a Naive Bayes graph.

Overrides:

buildStructure in class BayesNet

Throws:

java.lang.Exception

AddArcMakesSense

private boolean AddArcMakesSense(int iAttributeHead,
                                 int iAttributeTail)

AddArcMakesSense checks whether adding the arc from iAttributeTail to iAttributeHead does not already exists and does not introduce a cycle

Parameters:

iAttributeHead - index of the attribute that becomes head of the arrow

iAttributeTail - index of the attribute that becomes tail of the arrow

Returns:

true if adding arc is allowed, otherwise false

globalInfo

public java.lang.String globalInfo()

This will return a string describing the classifier.

Returns:

The string.

main

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

Main method for testing this class.

Parameters:

argv - the options