A Bayesian Approach to Learning Causal Networks

@inproceedings{Heckerman1995ABA,
  title={A Bayesian Approach to Learning Causal Networks},
  author={David Heckerman},
  booktitle={UAI},
  year={1995}
}
Whereas acausal Bayesian networks rep­ resent probabilistic independence, causal Bayesian networks represent causal relation­ ships. In this paper, we examine Bayesian methods for learning both types of networks. Bayesian methods for learning acausal net­ works are fairly well developed. These meth­ ods often employ assumptions to facilitate the construction of priors, including the as­ sumptions of parameter independence, pa­ rameter modularity, and likelihood equiva­ lence. We show that… CONTINUE READING
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