Factorization of computations in Bayesian networks: Interpretation of factors
Source of Publication
Springer Proceedings in Mathematics and Statistics
© Springer International Publishing Switzerland 2017. Given a Bayesian network (BN) relative to a set I of discrete random variables, we are interested in computing the probability distribution PS, where the target S is a subset of I. The general idea is to express PS in the form of a product of factors whereby each factor is easily computed and can be interpreted in terms of conditional probabilities. In this paper, a condition statingwhen PS can be written as a product of conditional probability distributions is called a non-pathology condition. This paper also considers an interpretation of the factors involved in computing marginal probabilities in BNs and a representation of the probability target as a Bayesian network of level two. Establishing such a factorization and interpretations is indeed interesting and relevant in the case of large BNs.
Springer New York LLC
Bayesian networks, Bayesian networks of level two, Inference, Pathological bayesian networks
Smail, Linda and Azouz, Zineb, "Factorization of computations in Bayesian networks: Interpretation of factors" (2017). All Works. 1638.
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