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.Comment: Appears in Proceedings of the Fourth Conference on Uncertainty in
Artificial Intelligence (UAI1988