Abstract
Given a Bayesian network (BN) relative to a set I of discrete random variables, we are interested in computing the probability distribution \(P_S\), where the target S is a subset of I. The general idea is to express \(P_{S}\) 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 stating when \(P_{S}\) 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.
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Smail, L., Azouz, Z. (2017). Factorization of Computations in Bayesian Networks: Interpretation of Factors. In: Abualrub, T., Jarrah, A., Kallel, S., Sulieman, H. (eds) Mathematics Across Contemporary Sciences. AUS-ICMS 2015. Springer Proceedings in Mathematics & Statistics, vol 190. Springer, Cham. https://doi.org/10.1007/978-3-319-46310-0_13
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