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java.lang.Objectweka.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.TabuSearch
public class TabuSearch
This Bayes Network learning algorithm uses tabu search for finding a well scoring Bayes network structure. Tabu search is hill climbing till an optimum is reached. The following step is the least worst possible step. The last X steps are kept in a list and none of the steps in this so called tabu list is considered in taking the next step. The best network found in this traversal is returned.
For more information see:
R.R. Bouckaert (1995). Bayesian Belief Networks: from Construction to Inference. Utrecht, Netherlands.
@phdthesis{Bouckaert1995, address = {Utrecht, Netherlands}, author = {R.R. Bouckaert}, institution = {University of Utrecht}, title = {Bayesian Belief Networks: from Construction to Inference}, year = {1995} }Valid options are:
-L <integer> Tabu list length
-U <integer> Number of runs
-P <nr of parents> Maximum number of parents
-R Use arc reversal operation. (default false)
-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)
Field Summary |
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Fields inherited from class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm |
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TAGS_CV_TYPE |
Constructor Summary | |
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TabuSearch()
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Method Summary | |
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java.lang.String[] |
getOptions()
Gets the current settings of the search algorithm. |
java.lang.String |
getRevision()
Returns the revision string. |
int |
getRuns()
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int |
getTabuList()
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TechnicalInformation |
getTechnicalInformation()
Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on. |
java.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()
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void |
setOptions(java.lang.String[] options)
Parses a given list of options. |
void |
setRuns(int nRuns)
Sets the number of runs |
void |
setTabuList(int nTabuList)
Sets the Tabu List length. |
java.lang.String |
tabuListTipText()
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Methods inherited from class weka.classifiers.bayes.net.search.global.HillClimber |
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getInitAsNaiveBayes, getMaxNrOfParents, getUseArcReversal, setInitAsNaiveBayes, setMaxNrOfParents, setUseArcReversal, useArcReversalTipText |
Methods inherited from class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm |
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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 |
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buildStructure, initAsNaiveBayesTipText, maxNrOfParentsTipText, toString |
Methods inherited from class java.lang.Object |
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equals, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Constructor Detail |
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public TabuSearch()
Method Detail |
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public TechnicalInformation getTechnicalInformation()
getTechnicalInformation
in interface TechnicalInformationHandler
public int getRuns()
public void setRuns(int nRuns)
nRuns
- The number of runs to setpublic int getTabuList()
public void setTabuList(int nTabuList)
nTabuList
- The nTabuList to setpublic java.util.Enumeration listOptions()
listOptions
in interface OptionHandler
listOptions
in class HillClimber
public void setOptions(java.lang.String[] options) throws java.lang.Exception
-L <integer> Tabu list length
-U <integer> Number of runs
-P <nr of parents> Maximum number of parents
-R Use arc reversal operation. (default false)
-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)
setOptions
in interface OptionHandler
setOptions
in class HillClimber
options
- the list of options as an array of strings
java.lang.Exception
- if an option is not supportedpublic java.lang.String[] getOptions()
getOptions
in interface OptionHandler
getOptions
in class HillClimber
public java.lang.String globalInfo()
globalInfo
in class HillClimber
public java.lang.String runsTipText()
public java.lang.String tabuListTipText()
public java.lang.String getRevision()
getRevision
in interface RevisionHandler
getRevision
in class HillClimber
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