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Variable elimination

Variable elimination (VE) is a simple and general exact inference algorithm in probabilistic graphical models, such as Bayesian networks and Markov random fields. It can be used for inference of maximum a posteriori (MAP) state or estimation of conditional or marginal distributions over a subset of variables. The algorithm has exponential time…

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Variable elimination

Nodes14
Edges13
Triples15
Avg. degree1.86
Density0.142857
Components1

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Variable elimination

Top relations

related to Inference · 10
Variable elimination → Algorithm, Bayesian, CPTs, More, SO, Taken, The, U-XE, VE, XE
related to Factors · 4
Variable elimination → Enabling, Joint, One, Thus

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Important terminology

displaystyle variable algorithm elimination variables factor phi factors inference ve conditional set distribution eliminate complexity order used also instantiation one

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
a probability distribution or conditional distributioninstance ofOne may perform operations on factors of different representations0.80text
Variable eliminationrelated to FactorsEnabling0.60section
Variable eliminationrelated to FactorsOne0.60section
Variable eliminationrelated to FactorsJoint0.60section
Variable eliminationrelated to FactorsThus0.60section
Variable eliminationrelated to InferenceThe0.60section
Variable eliminationrelated to InferenceVE0.60section
Variable eliminationrelated to InferenceTaken0.60section
Variable eliminationrelated to InferenceBayesian0.60section
Variable eliminationrelated to InferenceSO0.60section
Variable eliminationrelated to InferenceMore0.60section
Variable eliminationrelated to InferenceAlgorithm0.60section

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