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Constructing probabilistic models

delete1997-06-01
delete7
PRE
AI
R
Radim Jiroušek *
N
Nicholas Kushmerick
DOI：10.1016/S1386-5056(97)00026-9delete
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Abstract

Abstract

En 中文
Bayesian networks have become one of the most popular probabilistic techniques in AI, largely due to the development of several efficient inference algorithms. In this paper we describe a heuristic method for constructing Bayesian networks. Our construction method relies on the relationship between Bayesian networks and decomposable models, a special kind of graphical model. We explain this relationship and then show how it can be used to facilitate model construction. Finally, we describe an implemented computer program that illustrates these ideas. (C) 1997 Elsevier Science Ireland Ltd.
Keywords:
uncertainty
probability theory
graph models
Bayesian network
learning

Journal

International Journal of Medical Informatics cover
International Journal of Medical Informatics
IF:
4.1
Papers:
4.5K
Citations:
1.1W

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No organization information available