Bayesian Model Averaging Using the k-best Bayesian Network Structures

Details Bayesian Model Averaging Using the k-best Bayesian Network Structures Bayesian Model Averaging Using the k-best Bayesian Network Structures

2012-03-15

arxiv.org/abs/1203.3520v1

Computer Science

Learning

Appears in Proceedings of the Twenty-Sixth Conference on Uncertainty in Artificial Intelligence (UAI2010)

Scientific paper

We study the problem of learning Bayesian network structures from data. We develop an algorithm for finding the k-best Bayesian network structures. We propose to compute the posterior probabilities of hypotheses of interest by Bayesian model averaging over the k-best Bayesian networks. We present empirical results on structural discovery over several real and synthetic data sets and show that the method outperforms the model selection method and the state of-the-art MCMC methods.

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