Factorization of computations in Bayesian networks: Interpretation of factors

Document Type

Conference Proceeding

Source of Publication

Springer Proceedings in Mathematics and Statistics

Publication Date

1-1-2017

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.

ISBN

9783319463094

ISSN

2194-1009

Publisher

Springer New York LLC

Volume

190

First Page

207

Last Page

226

Disciplines

Mathematics

Keywords

Bayesian networks, Bayesian networks of level two, Inference, Pathological bayesian networks

Scopus ID

85012237700

Indexed in Scopus

yes

Open Access

no

Link to Full Text

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