An empirical analysis of likelihood-weighting simulation on a large, multiply-connected belief network

Shwe MA, Cooper GF. An empirical analysis of likelihood-weighting simulation on a large, multiply-connected belief network. Computers and Biomedical Research 24 (1991) 453–475.  PMID: 1743005

We analyzed the convergence properties of likelihoodweighting algorithms on a two-level, multiply connected, belief-network representation of the QMR knowledge base of internal medicine. Specifically, on two difficult diagnostic cases, we examined the effects of Markov blanket scoring, importance sampling, and self-importance sampling, demonstrating that the Markov blanket scoring and self-importance sampling significantly improve the convergence of the simulation on our model

Publication Year: 
1991
Faculty Author: 
Publication Credits: 
Shwe MA, Cooper GF.
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