public class TAN extends GlobalScoreSearchAlgorithm implements TechnicalInformationHandler
@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)
TAGS_CV_TYPE
Constructor and Description |
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TAN() |
Modifier and Type | Method and Description |
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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 Liu
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java.lang.String[] |
getOptions()
Gets the current settings of the Classifier.
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java.lang.String |
getRevision()
Returns the revision string.
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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.
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java.util.Enumeration |
listOptions()
Returns an enumeration describing the available options.
|
void |
setOptions(java.lang.String[] options)
Parses a given list of options.
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calcScore, calcScoreWithExtraParent, calcScoreWithMissingParent, calcScoreWithReversedParent, cumulativeCV, CVTypeTipText, getCVType, getMarkovBlanketClassifier, getUseProb, kFoldCV, leaveOneOutCV, markovBlanketClassifierTipText, setCVType, setMarkovBlanketClassifier, setUseProb, useProbTipText
initAsNaiveBayesTipText, maxNrOfParentsTipText, toString
public TechnicalInformation getTechnicalInformation()
getTechnicalInformation
in interface TechnicalInformationHandler
public void buildStructure(BayesNet bayesNet, Instances instances) throws java.lang.Exception
buildStructure
in class SearchAlgorithm
bayesNet
- instances
- java.lang.Exception
- if something goes wrongpublic java.util.Enumeration listOptions()
listOptions
in interface OptionHandler
listOptions
in class GlobalScoreSearchAlgorithm
public void setOptions(java.lang.String[] options) throws java.lang.Exception
-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 GlobalScoreSearchAlgorithm
options
- the list of options as an array of stringsjava.lang.Exception
- if an option is not supportedpublic java.lang.String[] getOptions()
getOptions
in interface OptionHandler
getOptions
in class GlobalScoreSearchAlgorithm
public java.lang.String globalInfo()
globalInfo
in class GlobalScoreSearchAlgorithm
public java.lang.String getRevision()
getRevision
in interface RevisionHandler
getRevision
in class GlobalScoreSearchAlgorithm