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Complexity of probabilistic inference in belief nets--an experimental study

There are three families of exact methods used for probabilistic inference in
belief nets. It is necessary to compare them and analyze the advantages and
the disadvantages of each algorithm, and know the time cost of making
inferences in a given belief network. This paper discusses the factors that
influence the computation time of each algorithm, presents the predictive model
of the time complexity for each algorithm and shows the statistical results of
testing the algorithms with randomly generated belief networks. / Graduation date: 1991

Identiferoai:union.ndltd.org:ORGSU/oai:ir.library.oregonstate.edu:1957/37963
Date16 November 1990
CreatorsLi, Zhaoyu
ContributorsD'Ambrosio, Bruce D.
Source SetsOregon State University
Languageen_US
Detected LanguageEnglish
TypeThesis/Dissertation

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