weka.classifiers.bayes.net.search.global
Class RepeatedHillClimber

java.lang.Object
  weka.classifiers.bayes.net.search.SearchAlgorithm
      weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
          weka.classifiers.bayes.net.search.global.HillClimber
              weka.classifiers.bayes.net.search.global.RepeatedHillClimber

All Implemented Interfaces:

Serializable, OptionHandler, RevisionHandler

public class RepeatedHillClimber
extends HillClimber

This Bayes Network learning algorithm repeatedly uses hill climbing starting with a randomly generated network structure and return the best structure of the various runs.

Valid options are:

 -U <integer>
  Number of runs

 -A <seed>
  Random number seed

 -P <nr of parents>
  Maximum number of parents

 -R
  Use arc reversal operation.
  (default false)

 -N
  Initial structure is empty (instead of Naive Bayes)

 -mbc
  Applies a Markov Blanket correction to the network structure, 
  after a network structure is learned. This ensures that all 
  nodes in the network are part of the Markov blanket of the 
  classifier node.

 -S [LOO-CV|k-Fold-CV|Cumulative-CV]
  Score type (LOO-CV,k-Fold-CV,Cumulative-CV)

 -Q
  Use probabilistic or 0/1 scoring.
  (default probabilistic scoring)

Version:

$Revision: 8034 $

Author:

Remco Bouckaert ([email protected])

See Also:

Serialized Form

Field Summary

Fields inherited from class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm

TAGS_CV_TYPE

Constructor Summary

RepeatedHillClimber()

Method Summary

String[]	getOptions() Gets the current settings of the search algorithm.
String	getRevision() Returns the revision string.
int	getRuns() Returns the number of runs
int	getSeed() Returns the random seed
String	globalInfo() This will return a string describing the classifier.
Enumeration	listOptions() Returns an enumeration describing the available options.
String	runsTipText()
String	seedTipText()
void	setOptions(String[] options) Parses a given list of options.
void	setRuns(int nRuns) Sets the number of runs
void	setSeed(int nSeed) Sets the random number seed

Methods inherited from class weka.classifiers.bayes.net.search.global.HillClimber

getInitAsNaiveBayes, getMaxNrOfParents, getUseArcReversal, setInitAsNaiveBayes, setMaxNrOfParents, setUseArcReversal, useArcReversalTipText

Methods inherited from class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm

calcScore, calcScoreWithExtraParent, calcScoreWithMissingParent, calcScoreWithReversedParent, cumulativeCV, CVTypeTipText, getCVType, getMarkovBlanketClassifier, getUseProb, kFoldCV, leaveOneOutCV, markovBlanketClassifierTipText, setCVType, setMarkovBlanketClassifier, setUseProb, useProbTipText

Methods inherited from class weka.classifiers.bayes.net.search.SearchAlgorithm

buildStructure, initAsNaiveBayesTipText, maxNrOfParentsTipText, toString

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

RepeatedHillClimber

public RepeatedHillClimber()

Method Detail

getRuns

public int getRuns()

Returns the number of runs

Returns:

number of runs

setRuns

public void setRuns(int nRuns)

Sets the number of runs

Parameters:

nRuns - The number of runs to set

getSeed

public int getSeed()

Returns the random seed

Returns:

random number seed

setSeed

public void setSeed(int nSeed)

Sets the random number seed

Parameters:

nSeed - The number of the seed to set

listOptions

public Enumeration listOptions()

Returns an enumeration describing the available options.

Specified by:

listOptions in interface OptionHandler

Overrides:

listOptions in class HillClimber

Returns:

an enumeration of all the available options.

setOptions

public void setOptions(String[] options)
                throws Exception

Parses a given list of options.

Valid options are:

 -U <integer>
  Number of runs

 -A <seed>
  Random number seed

 -P <nr of parents>
  Maximum number of parents

 -R
  Use arc reversal operation.
  (default false)

 -N
  Initial structure is empty (instead of Naive Bayes)

 -mbc
  Applies a Markov Blanket correction to the network structure, 
  after a network structure is learned. This ensures that all 
  nodes in the network are part of the Markov blanket of the 
  classifier node.

 -S [LOO-CV|k-Fold-CV|Cumulative-CV]
  Score type (LOO-CV,k-Fold-CV,Cumulative-CV)

 -Q
  Use probabilistic or 0/1 scoring.
  (default probabilistic scoring)

Specified by:

setOptions in interface OptionHandler

Overrides:

setOptions in class HillClimber

Parameters:

options - the list of options as an array of strings

Throws:

Exception - if an option is not supported

getOptions

public String[] getOptions()

Gets the current settings of the search algorithm.

Specified by:

getOptions in interface OptionHandler

Overrides:

getOptions in class HillClimber

Returns:

an array of strings suitable for passing to setOptions

globalInfo

public String globalInfo()

This will return a string describing the classifier.

Overrides:

globalInfo in class HillClimber

Returns:

The string.

runsTipText

public String runsTipText()

Returns:

a string to describe the Runs option.

seedTipText

public String seedTipText()

Returns:

a string to describe the Seed option.

getRevision

public String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Overrides:

getRevision in class HillClimber

Returns:

the revision