C# Class AIMA.Core.Probability.BayesNet

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Méthodes publiques

Méthode	Description
BayesNet ( BayesNetNode root ) : AIMA.Core.Util
BayesNet ( BayesNetNode root1, BayesNetNode root2 ) : AIMA.Core.Util
BayesNet ( BayesNetNode root1, BayesNetNode root2, BayesNetNode root3 ) : AIMA.Core.Util
BayesNet ( List rootNodes ) : AIMA.Core.Util
getPriorSample ( ) : bool>.Dictionary
getPriorSample ( Randomizer r ) : bool>.Dictionary
getVariables ( ) : List
likelihoodWeighting ( String X, bool>.Dictionary evidence, int numberOfSamples ) : double[]
likelihoodWeighting ( String X, bool>.Dictionary evidence, int numberOfSamples, Randomizer r ) : double[]
mcmcAsk ( String X, bool>.Dictionary evidence, int numberOfVariables ) : double[]
mcmcAsk ( String X, bool>.Dictionary evidence, int numberOfVariables, Randomizer r ) : double[]
probabilityOf ( String Y, bool value, bool>.Dictionary evidence ) : double
rejectionSample ( String X, bool>.Dictionary evidence, int numberOfSamples ) : double[]
rejectionSample ( String X, bool>.Dictionary evidence, int numberOfSamples, Randomizer r ) : double[]

Private Methods

Méthode	Description
consistent ( bool>.Dictionary sample, bool>.Dictionary evidence ) : bool
createMBValues ( List markovBlanket, bool>.Dictionary evt ) : bool>.Dictionary
createRandomEvent ( List nonEvidenceVariables, bool>.Dictionary evidence, Randomizer r ) : bool>.Dictionary
getNodeOf ( String y ) : BayesNetNode
getVariableNodes ( ) : List
markovBlanket ( BayesNetNode node ) : List
markovBlanket ( BayesNetNode node, List soFar ) : List
nonEvidenceVariables ( bool>.Dictionary evidence, String query ) : List
truthValue ( double ds, Randomizer r ) : bool

Method Details

BayesNet() public méthode

public BayesNet ( BayesNetNode root ) : AIMA.Core.Util
root	BayesNetNode
Résultat	AIMA.Core.Util

BayesNet() public méthode

public BayesNet ( BayesNetNode root1, BayesNetNode root2 ) : AIMA.Core.Util
root1	BayesNetNode
root2	BayesNetNode
Résultat	AIMA.Core.Util

BayesNet() public méthode

public BayesNet ( BayesNetNode root1, BayesNetNode root2, BayesNetNode root3 ) : AIMA.Core.Util
root1	BayesNetNode
root2	BayesNetNode
root3	BayesNetNode
Résultat	AIMA.Core.Util

BayesNet() public méthode

public BayesNet ( List rootNodes ) : AIMA.Core.Util
rootNodes	List
Résultat	AIMA.Core.Util

getPriorSample() public méthode

public getPriorSample ( ) : bool>.Dictionary
Résultat	bool>.Dictionary

getPriorSample() public méthode

public getPriorSample ( Randomizer r ) : bool>.Dictionary
r	Randomizer
Résultat	bool>.Dictionary

getVariables() public méthode

public getVariables ( ) : List
Résultat	List

likelihoodWeighting() public méthode

public likelihoodWeighting ( String X, bool>.Dictionary evidence, int numberOfSamples ) : double[]
X	String
evidence	bool>.Dictionary
numberOfSamples	int
Résultat	double[]

likelihoodWeighting() public méthode

public likelihoodWeighting ( String X, bool>.Dictionary evidence, int numberOfSamples, Randomizer r ) : double[]
X	String
evidence	bool>.Dictionary
numberOfSamples	int
r	Randomizer
Résultat	double[]

mcmcAsk() public méthode

public mcmcAsk ( String X, bool>.Dictionary evidence, int numberOfVariables ) : double[]
X	String
evidence	bool>.Dictionary
numberOfVariables	int
Résultat	double[]

mcmcAsk() public méthode

public mcmcAsk ( String X, bool>.Dictionary evidence, int numberOfVariables, Randomizer r ) : double[]
X	String
evidence	bool>.Dictionary
numberOfVariables	int
r	Randomizer
Résultat	double[]

probabilityOf() public méthode

public probabilityOf ( String Y, bool value, bool>.Dictionary evidence ) : double
Y	String
value	bool
evidence	bool>.Dictionary
Résultat	double

rejectionSample() public méthode

public rejectionSample ( String X, bool>.Dictionary evidence, int numberOfSamples ) : double[]
X	String
evidence	bool>.Dictionary
numberOfSamples	int
Résultat	double[]

rejectionSample() public méthode

public rejectionSample ( String X, bool>.Dictionary evidence, int numberOfSamples, Randomizer r ) : double[]
X	String
evidence	bool>.Dictionary
numberOfSamples	int
r	Randomizer
Résultat	double[]