Structure Variability in Bayesian Networks

Details Structure Variability in Bayesian Networks Structure Variability in Bayesian Networks

2009-09-09

arxiv.org/abs/0909.1685v4

Statistics

Methodology

21 pages, 4 figures

Scientific paper

The structure of a Bayesian network encodes most of the information about the probability distribution of the data, which is uniquely identified given some general distributional assumptions. Therefore it's important to study the variability of its network structure, which can be used to compare the performance of different learning algorithms and to measure the strength of any arbitrary subset of arcs. In this paper we will introduce some descriptive statistics and the corresponding parametric and Monte Carlo tests on the undirected graph underlying the structure of a Bayesian network, modeled as a multivariate Bernoulli random variable.

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