C# 클래스 AIMA.Core.Probability.BayesNet

파일 보기 프로젝트 열기: PaulMineau/AIMA.Net 1 사용 예제들

공개 메소드들

메소드 설명
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[]

비공개 메소드들

메소드 설명
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

메소드 상세

BayesNet() 공개 메소드

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

BayesNet() 공개 메소드

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

BayesNet() 공개 메소드

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

BayesNet() 공개 메소드

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

getPriorSample() 공개 메소드

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

getPriorSample() 공개 메소드

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

getVariables() 공개 메소드

public getVariables ( ) : List
리턴 List

likelihoodWeighting() 공개 메소드

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

likelihoodWeighting() 공개 메소드

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

mcmcAsk() 공개 메소드

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

mcmcAsk() 공개 메소드

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

probabilityOf() 공개 메소드

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

rejectionSample() 공개 메소드

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

rejectionSample() 공개 메소드

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