Class TAN
- 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.TAN
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- All Implemented Interfaces:
java.io.Serializable
,OptionHandler
,RevisionHandler
,TechnicalInformationHandler
public class TAN extends GlobalScoreSearchAlgorithm implements TechnicalInformationHandler
This Bayes Network learning algorithm determines the maximum weight spanning tree and returns a Naive Bayes network augmented with a tree.
For more information see:
N. Friedman, D. Geiger, M. Goldszmidt (1997). Bayesian network classifiers. Machine Learning. 29(2-3):131-163. BibTeX:@article{Friedman1997, author = {N. Friedman and D. Geiger and M. Goldszmidt}, journal = {Machine Learning}, number = {2-3}, pages = {131-163}, title = {Bayesian network classifiers}, volume = {29}, year = {1997} }
Valid options are:-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: 1.7 $
- Author:
- Remco Bouckaert
- 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 TAN()
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description void
buildStructure(BayesNet bayesNet, Instances instances)
buildStructure determines the network structure/graph of the network using the maximimum weight spanning tree algorithm of Chow and Liujava.lang.String[]
getOptions()
Gets the current settings of the Classifier.java.lang.String
getRevision()
Returns the revision string.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.void
setOptions(java.lang.String[] options)
Parses a given list of options.-
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
initAsNaiveBayesTipText, maxNrOfParentsTipText, toString
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Method Detail
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getTechnicalInformation
public 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.- Specified by:
getTechnicalInformation
in interfaceTechnicalInformationHandler
- Returns:
- the technical information about this class
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buildStructure
public void buildStructure(BayesNet bayesNet, Instances instances) throws java.lang.Exception
buildStructure determines the network structure/graph of the network using the maximimum weight spanning tree algorithm of Chow and Liu- Overrides:
buildStructure
in classSearchAlgorithm
- Parameters:
bayesNet
-instances
-- Throws:
java.lang.Exception
- if something goes wrong
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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 classGlobalScoreSearchAlgorithm
- 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:-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 classGlobalScoreSearchAlgorithm
- 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 Classifier.- Specified by:
getOptions
in interfaceOptionHandler
- Overrides:
getOptions
in classGlobalScoreSearchAlgorithm
- 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 classGlobalScoreSearchAlgorithm
- Returns:
- The string.
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getRevision
public java.lang.String getRevision()
Returns the revision string.- Specified by:
getRevision
in interfaceRevisionHandler
- Overrides:
getRevision
in classGlobalScoreSearchAlgorithm
- Returns:
- the revision
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