Title

Factorization of computations in Bayesian networks: Interpretation of factors

Source of Publication

Springer Proceedings in Mathematics and Statistics

Abstract

© 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.

Document Type

Conference Proceeding

ISBN

['9783319463094']

First Page

207

Last Page

226

Publication Date

1-1-2017

DOI

10.1007/978-3-319-46310-0_13

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