weka.classifiers.bayes.net.search.local

Class RepeatedHillClimber

java.lang.Object

weka.classifiers.bayes.net.search.SearchAlgorithm

weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm

weka.classifiers.bayes.net.search.local.HillClimber

weka.classifiers.bayes.net.search.local.RepeatedHillClimber

All Implemented Interfaces:

java.io.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 [BAYES|MDL|ENTROPY|AIC|CROSS_CLASSIC|CROSS_BAYES]
  Score type (BAYES, BDeu, MDL, ENTROPY and AIC)
 

Version:

$Revision: 10154 $

Author:

Remco Bouckaert (rrb@xm.co.nz)

See Also:

Serialized Form

Field Summary

Fields inherited from class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm

TAGS_SCORE_TYPE

Constructor Summary

Constructors

Constructor and Description
RepeatedHillClimber()

Method Summary

Modifier and Type	Method and Description
java.lang.String[]	getOptions() Gets the current settings of the search algorithm.
java.lang.String	getRevision() Returns the revision string.
int	getRuns()
int	getSeed()
java.lang.String	globalInfo() This will return a string describing the classifier.
java.util.Enumeration<Option>	listOptions() Returns an enumeration describing the available options.
java.lang.String	runsTipText()
java.lang.String	seedTipText()
void	setOptions(java.lang.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.local.HillClimber

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

Methods inherited from class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm

buildStructure, calcNodeScore, calcScoreWithExtraParent, calcScoreWithMissingParent, getMarkovBlanketClassifier, getScoreType, logScore, markovBlanketClassifierTipText, scoreTypeTipText, setMarkovBlanketClassifier, setScoreType

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

initAsNaiveBayesTipText, maxNrOfParentsTipText, toString

Methods inherited from class java.lang.Object

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

Methods inherited from interface weka.core.OptionHandler

makeCopy

Constructor Detail

RepeatedHillClimber

public RepeatedHillClimber()

Method Detail

getRuns

public int getRuns()

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:

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 java.util.Enumeration<Option> 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(java.lang.String[] options)
                throws java.lang.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 [BAYES|MDL|ENTROPY|AIC|CROSS_CLASSIC|CROSS_BAYES]
  Score type (BAYES, BDeu, MDL, ENTROPY and AIC)
 

Specified by:

setOptions in interface OptionHandler

Overrides:

setOptions in class HillClimber

Parameters:

options - the list of options as an array of strings

Throws:

java.lang.Exception - if an option is not supported

getOptions

public java.lang.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 java.lang.String globalInfo()

This will return a string describing the classifier.

Overrides:

globalInfo in class HillClimber

Returns:

The string.

runsTipText

public java.lang.String runsTipText()

Returns:

a string to describe the Runs option.

seedTipText

public java.lang.String seedTipText()

Returns:

a string to describe the Seed option.

getRevision

public java.lang.String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Overrides:

getRevision in class HillClimber

Returns:

the revision