Partial Order MCMC for Structure Discovery in Bayesian Networks

Details Partial Order MCMC for Structure Discovery in Bayesian Networks Partial Order MCMC for Structure Discovery in Bayesian Networks

2012-02-14

arxiv.org/abs/1202.3753v1

Computer Science

Learning

Scientific paper

We present a new Markov chain Monte Carlo method for estimating posterior probabilities of structural features in Bayesian networks. The method draws samples from the posterior distribution of partial orders on the nodes; for each sampled partial order, the conditional probabilities of interest are computed exactly. We give both analytical and empirical results that suggest the superiority of the new method compared to previous methods, which sample either directed acyclic graphs or linear orders on the nodes.

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