Bayesian DAG Construction from Conditional Independencies
نویسندگان
چکیده
To build a Bayesian network, one may directly construct a directed acyclic graph (DAG) based on causal relationship of the domain variables. However, it may be necessary in many applications to construct a DAG from conditional independencies (CIs). In this paper, we characterize CIs that can be represented by a perfect DAG and suggest an algorithm to construct such a DAG, provided that the given set of CIs satisfy certain conditions. We discuss the advantages of our method and compare it with the algorithm proposed by Verma.
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