Learning Bayesian Networks

  title={Learning Bayesian Networks},
  author={David Heckerman and Dan Geiger},
We examine Bayesian methods for learning Bayesian networks from a combination of prior knowledge and statistical data. In particular, we develop simple methods for generating priors for Bayesian-network parameters. Our work is a generalization of previous work that has concentrated on Bayesian networks containing only discrete variables and (to a lesser extent) on Gaussian networks. We introduce three assumptions that are abstractions of previously made assumptions: likelihood equivalence… CONTINUE READING
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