Uncertainty in Artificial Intelligence
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An Empirical Comparison of Three Inference Methods
David Heckerman
Abstract:
In this paper, an empirical evaluation of three inference methods for uncertain reasoning is presented in the context of Pathfinder, a large expert system for the diagnosis of lymph-node pathology. The inference procedures evaluated are (1) Bayes' theorem, assuming evidence is conditionally independent given each hypothesis; (2) odds-likelihood updating, assuming evidence is conditionally independent given each hypothesis and given the negation of each hypothesis; and (3) a inference method related to the Dempster-Shafer theory of belief. Both expert-rating and decision-theoretic metrics are used to compare the diagnostic accuracy of the inference methods.
Keywords: null
Pages: 283-302
PS Link:
PDF Link: /papers/88/p283-heckerman.pdf
BibTex:
@INPROCEEDINGS{Heckerman88,
AUTHOR = "David Heckerman ",
TITLE = "An Empirical Comparison of Three Inference Methods",
BOOKTITLE = "Uncertainty in Artificial Intelligence 4 Annual Conference on Uncertainty in Artificial Intelligence (UAI-88)",
PUBLISHER = "Elsevier Science",
ADDRESS = "Amsterdam, NL",
YEAR = "1988",
PAGES = "283--302"
}


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