Uncertainty in Artificial Intelligence
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A Bayesian Method Reexamined
Derek Ayers
Abstract:
This paper examines the "K2" network scoring metric of Cooper and Herskovits. It shows counterintuitive results from applying this metric to simple networks. One family of noninformative priors is suggested for assigning equal scores to equivalent networks.
Keywords:
Pages: 23-27
PS Link:
PDF Link: /papers/94/p23-ayers.pdf
BibTex:
@INPROCEEDINGS{Ayers94,
AUTHOR = "Derek Ayers ",
TITLE = "A Bayesian Method Reexamined",
BOOKTITLE = "Proceedings of the Tenth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-94)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1994",
PAGES = "23--27"
}


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