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A note on minimal d-separation trees for structural learning
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DOI：10.1016/j.artint.2010.01.002.png)
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摘要
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Structural learning of a Bayesian network is often decomposed into problems related to its subgraphs, although many approaches without decomposition were proposed. In 2006, Xie, Geng and Zhao proposed using a d-separation tree to improve the power of conditional independence tests and the efficiency of structural learning. In our research note, we study a minimal d-separation tree under a partial ordering, by which the maximal efficiency can be obtained. Our results demonstrate that a minimal cl-separation tree of a directed acyclic graph (DAG) can be constructed by searching for the clique tree of a minimal triangulation of the moral graph for the DAG. (C) 2010 Elsevier B.V. All rights reserved.
Keyword:
Bayesian network
Clique tree
Minimal d-separation tree
Minimal triangulation
Separation tree
Structural learning
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