Uncertainty in Artificial Intelligence
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A Transformational Characterization of Equivalent Bayesian Network Structures
David Chickering
Abstract:
We present a simple characterization of equivalent Bayesian network structures based on local transformations. The significance of the characterization is twofold. First, we are able to easily prove several new invariant properties of theoretical interest for equivalent structures. Second, we use the characterization to derive an efficient algorithm that identifies all of the compelled edges in a structure. Compelled edge identification is of particular importance for learning Bayesian network structures from data because these edges indicate causal relationships when certain assumptions hold.
Keywords:
Pages: 87-98
PS Link:
PDF Link: /papers/95/p87-chickering.pdf
BibTex:
@INPROCEEDINGS{Chickering95,
AUTHOR = "David Chickering ",
TITLE = "A Transformational Characterization of Equivalent Bayesian Network Structures",
BOOKTITLE = "Proceedings of the Eleventh Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-95)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1995",
PAGES = "87--98"
}


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