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
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: 10154 $
- Author:
- Remco Bouckaert (rrb@xm.co.nz)
- See Also:
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Field Summary
Fields inherited from class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
TAGS_CV_TYPE -
Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionString[]Gets the current settings of the search algorithm.Returns the revision string.intgetRuns()Returns the number of runsintgetSeed()Returns the random seedThis will return a string describing the classifier.Returns an enumeration describing the available options.voidsetOptions(String[] options) Parses a given list of options.voidsetRuns(int nRuns) Sets the number of runsvoidsetSeed(int nSeed) Sets the random number seedMethods inherited from class weka.classifiers.bayes.net.search.global.HillClimber
getInitAsNaiveBayes, getMaxNrOfParents, getUseArcReversal, setInitAsNaiveBayes, setMaxNrOfParents, setUseArcReversal, useArcReversalTipTextMethods 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, useProbTipTextMethods inherited from class weka.classifiers.bayes.net.search.SearchAlgorithm
buildStructure, initAsNaiveBayesTipText, maxNrOfParentsTipText, toString
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Constructor Details
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RepeatedHillClimber
public RepeatedHillClimber()
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Method Details
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getRuns
public int getRuns()Returns the number of runs- Returns:
- number of runs
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setRuns
public void setRuns(int nRuns) Sets the number of runs- Parameters:
nRuns- The number of runs to set
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getSeed
public int getSeed()Returns the random seed- Returns:
- random number seed
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setSeed
public void setSeed(int nSeed) Sets the random number seed- Parameters:
nSeed- The number of the seed to set
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listOptions
Returns an enumeration describing the available options.- Specified by:
listOptionsin interfaceOptionHandler- Overrides:
listOptionsin classHillClimber- Returns:
- an enumeration of all the available options.
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setOptions
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:
setOptionsin interfaceOptionHandler- Overrides:
setOptionsin classHillClimber- Parameters:
options- the list of options as an array of strings- Throws:
Exception- if an option is not supported
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getOptions
Gets the current settings of the search algorithm.- Specified by:
getOptionsin interfaceOptionHandler- Overrides:
getOptionsin classHillClimber- Returns:
- an array of strings suitable for passing to setOptions
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globalInfo
This will return a string describing the classifier.- Overrides:
globalInfoin classHillClimber- Returns:
- The string.
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runsTipText
- Returns:
- a string to describe the Runs option.
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seedTipText
- Returns:
- a string to describe the Seed option.
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getRevision
Returns the revision string.- Specified by:
getRevisionin interfaceRevisionHandler- Overrides:
getRevisionin classHillClimber- Returns:
- the revision
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