Class RepeatedHillClimber
- java.lang.Object
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- weka.classifiers.bayes.net.search.SearchAlgorithm
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- weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
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- weka.classifiers.bayes.net.search.global.HillClimber
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- weka.classifiers.bayes.net.search.global.RepeatedHillClimber
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- 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 [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: 1.6 $
- Author:
- Remco Bouckaert (rrb@xm.co.nz)
- See Also:
- Serialized Form
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Field Summary
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Fields inherited from class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
TAGS_CV_TYPE
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Constructor Summary
Constructors Constructor Description RepeatedHillClimber()
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description java.lang.String[]
getOptions()
Gets the current settings of the search algorithm.java.lang.String
getRevision()
Returns the revision string.int
getRuns()
Returns the number of runsint
getSeed()
Returns the random seedjava.lang.String
globalInfo()
This will return a string describing the classifier.java.util.Enumeration
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 runsvoid
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
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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
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Methods inherited from class weka.classifiers.bayes.net.search.SearchAlgorithm
buildStructure, initAsNaiveBayesTipText, maxNrOfParentsTipText, toString
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Method Detail
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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
public java.util.Enumeration listOptions()
Returns an enumeration describing the available options.- Specified by:
listOptions
in interfaceOptionHandler
- Overrides:
listOptions
in classHillClimber
- Returns:
- an enumeration of all the available options.
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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 [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 interfaceOptionHandler
- Overrides:
setOptions
in classHillClimber
- Parameters:
options
- the list of options as an array of strings- Throws:
java.lang.Exception
- if an option is not supported
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getOptions
public java.lang.String[] getOptions()
Gets the current settings of the search algorithm.- Specified by:
getOptions
in interfaceOptionHandler
- Overrides:
getOptions
in classHillClimber
- Returns:
- an array of strings suitable for passing to setOptions
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globalInfo
public java.lang.String globalInfo()
This will return a string describing the classifier.- Overrides:
globalInfo
in classHillClimber
- Returns:
- The string.
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runsTipText
public java.lang.String runsTipText()
- Returns:
- a string to describe the Runs option.
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seedTipText
public java.lang.String seedTipText()
- Returns:
- a string to describe the Seed option.
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getRevision
public java.lang.String getRevision()
Returns the revision string.- Specified by:
getRevision
in interfaceRevisionHandler
- Overrides:
getRevision
in classHillClimber
- Returns:
- the revision
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