Class LAGDHillClimber
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.LAGDHillClimber
- All Implemented Interfaces:
Serializable,OptionHandler,RevisionHandler
This Bayes Network learning algorithm uses a Look
Ahead Hill Climbing algorithm called LAGD Hill Climbing. Unlike Greedy Hill
Climbing it doesn't calculate a best greedy operation (adding, deleting or
reversing an arc) but a sequence of nrOfLookAheadSteps operations, which
leads to a network structure whose score is most likely higher in comparison
to the network obtained by performing a sequence of nrOfLookAheadSteps greedy
operations. The search is not restricted by an order on the variables (unlike
K2). The difference with B and B2 is that this hill climber also considers
arrows part of the naive Bayes structure for deletion.
Valid options are:
-L <nr of look ahead steps> Look Ahead Depth
-G <nr of good operations> Nr of Good Operations
-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:
- Manuel Neubach
- See Also:
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Field Summary
Fields inherited from class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
TAGS_SCORE_TYPE -
Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionintGets the max number of parents.intGets the number of "good operations"intGets the number of look-ahead stepsString[]Gets the current settings of the search algorithm.Returns the revision string.This will return a string describing the search algorithm.Returns an enumeration describing the available options.voidsetMaxNrOfParents(int nMaxNrOfParents) Sets the max number of parentsvoidsetNrOfGoodOperations(int nNrOfGoodOperations) Sets the number of "good operations"voidsetNrOfLookAheadSteps(int nNrOfLookAheadSteps) Sets the number of look-ahead stepsvoidsetOptions(String[] options) Parses a given list of options.Methods inherited from class weka.classifiers.bayes.net.search.local.HillClimber
getInitAsNaiveBayes, getUseArcReversal, setInitAsNaiveBayes, setUseArcReversal, useArcReversalTipTextMethods inherited from class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
buildStructure, calcNodeScore, calcScoreWithExtraParent, calcScoreWithMissingParent, getMarkovBlanketClassifier, getScoreType, logScore, markovBlanketClassifierTipText, scoreTypeTipText, setMarkovBlanketClassifier, setScoreTypeMethods inherited from class weka.classifiers.bayes.net.search.SearchAlgorithm
initAsNaiveBayesTipText, maxNrOfParentsTipText, toString
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Constructor Details
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LAGDHillClimber
public LAGDHillClimber()
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Method Details
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setMaxNrOfParents
public void setMaxNrOfParents(int nMaxNrOfParents) Sets the max number of parents- Overrides:
setMaxNrOfParentsin classHillClimber- Parameters:
nMaxNrOfParents- the max number of parents
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getMaxNrOfParents
public int getMaxNrOfParents()Gets the max number of parents.- Overrides:
getMaxNrOfParentsin classHillClimber- Returns:
- the max number of parents
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setNrOfLookAheadSteps
public void setNrOfLookAheadSteps(int nNrOfLookAheadSteps) Sets the number of look-ahead steps- Parameters:
nNrOfLookAheadSteps- the number of look-ahead steps
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getNrOfLookAheadSteps
public int getNrOfLookAheadSteps()Gets the number of look-ahead steps- Returns:
- the number of look-ahead step
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setNrOfGoodOperations
public void setNrOfGoodOperations(int nNrOfGoodOperations) Sets the number of "good operations"- Parameters:
nNrOfGoodOperations- the number of "good operations"
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getNrOfGoodOperations
public int getNrOfGoodOperations()Gets the number of "good operations"- Returns:
- the number of "good operations"
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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:Valid options are:
-L <nr of look ahead steps> Look Ahead Depth
-G <nr of good operations> Nr of Good Operations
-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:
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 search algorithm.- Overrides:
globalInfoin classHillClimber- Returns:
- The string.
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nrOfLookAheadStepsTipText
- Returns:
- a string to describe the Number of Look Ahead Steps option.
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nrOfGoodOperationsTipText
- Returns:
- a string to describe the Number of Good Operations option.
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getRevision
Returns the revision string.- Specified by:
getRevisionin interfaceRevisionHandler- Overrides:
getRevisionin classHillClimber- Returns:
- the revision
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