8.1.2-QueryingProbabilityDistributions

# 8.1.2-QueryingProbabilityDistributions - Machine Learning...

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Machine Learning Srihari 1 Querying Probabilistic Graphical Models Sargur Srihari

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Machine Learning Srihari Probabilistic Graphical Models 2 CPDs: Joint Distribution : P ( X i | pa ( X i )) P ( X ) = P ( X i | pa ( X i )) i = 1 N P ( X ) = P ( X 1 ,.. X n ) P ( D , I , G , S , L ) = P ( D ) P ( I ) P ( G | D , I ) P ( S | I ) P ( L | G ) Represent joint probability distributions over multiple variables in terms of conditional probability distributions(CPDs) Resulting in great savings in no of parameters needed
Machine Learning Srihari 3 Queries of Interest • Probabilistic Graphical Models represent joint probability distributions over multiple variables • Their use is to answer queries of interest • This is called “inference” • What types of queries are there?

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Machine Learning Srihari Query Types 1. Probability Queries 2. MAP Queries Maximum a posteriori probability Also called MPE (Most Probable Explanation) 3. Marginal MAP Queries 4
Machine Learning Srihari Probability Queries • Most common type of query is a probability query • Query has two parts

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8.1.2-QueryingProbabilityDistributions - Machine Learning...

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