A Bayesian method reexamined

Authors:
Derek D. Ayers
Affiliations:
Department of Engineering-Economic Systems, Stanford University, Stanford, CA
Venue:
UAI'94 Proceedings of the Tenth international conference on Uncertainty in artificial intelligence
Year:
1994

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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.