Package edu.cmu.tetrad.search.score
Class GicScores
java.lang.Object
edu.cmu.tetrad.search.score.GicScores
- All Implemented Interfaces:
Score
Implements scores motivated by the Generalized Information Criterion (GIC) approach as given in Kim et al. (2012).
Kim, Y., Kwon, S., & Choi, H. (2012). Consistent model selection criteria on high dimensions. The Journal of Machine Learning Research, 13(1), 1037-1057.
As for all scores in Tetrad, higher scores mean more dependence, and negative scores indicate independence.
- Author:
- josephramsey
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Nested Class Summary
Nested ClassesModifier and TypeClassDescriptionstatic enumGives the options for the rules to use for calculating the scores. -
Constructor Summary
ConstructorsConstructorDescriptionConstructs the score using a covariance matrix.GicScores(ICovarianceMatrix covariances) Constructs the score using a covariance matrix. -
Method Summary
Modifier and TypeMethodDescriptionbooleandetermines(List<Node> z, Node y) Specialized scoring method for a single parent.intdoubleintThe sample size of the data.The variables of the score.booleanisEffectEdge(double bump) booleandoublelocalScore(int i, int... parents) The score of a node given its parents.doublelocalScoreDiff(int x, int y, int[] z) voidsetLambda(double lambda) voidsetPenaltyDiscount(double penaltyDiscount) voidsetRuleType(GicScores.RuleType ruleType) voidsetVariables(List<Node> variables) voidsetVerbose(boolean verbose) toString()A string representation of the score.Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, waitMethods inherited from interface edu.cmu.tetrad.search.score.Score
append, getVariable, localScore, localScore, localScoreDiff
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Constructor Details
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GicScores
Constructs the score using a covariance matrix. -
GicScores
Constructs the score using a covariance matrix.
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Method Details
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localScoreDiff
public double localScoreDiff(int x, int y, int[] z) - Specified by:
localScoreDiffin interfaceScore
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localScore
public double localScore(int i, int... parents) Description copied from interface:ScoreThe score of a node given its parents.- Specified by:
localScorein interfaceScore- Parameters:
i- The node.parents- The parents.- Returns:
- The score.
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getCovariances
Specialized scoring method for a single parent. Used to speed up the effect edges search. -
getSampleSize
public int getSampleSize()Description copied from interface:ScoreThe sample size of the data.- Specified by:
getSampleSizein interfaceScore- Returns:
- This size.
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isEffectEdge
public boolean isEffectEdge(double bump) - Specified by:
isEffectEdgein interfaceScore
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getDataSet
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isVerbose
public boolean isVerbose() -
setVerbose
public void setVerbose(boolean verbose) -
getVariables
Description copied from interface:ScoreThe variables of the score.- Specified by:
getVariablesin interfaceScore- Returns:
- This list.
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setVariables
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getMaxDegree
public int getMaxDegree()- Specified by:
getMaxDegreein interfaceScore
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determines
- Specified by:
determinesin interfaceScore
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setRuleType
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setLambda
public void setLambda(double lambda) -
getPenaltyDiscount
public double getPenaltyDiscount() -
setPenaltyDiscount
public void setPenaltyDiscount(double penaltyDiscount) -
toString
Description copied from interface:ScoreA string representation of the score.
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