论文信息 - Irrelevance and Parameter Learning in Bayesian Networks

Irrelevance and Parameter Learning in Bayesian Networks

It is possible to learn the parameters of a given Bayesian network structure from data because those parameters in(cid:0)uence the proba(cid:1) bility of observing the data(cid:2) However(cid:3) some of the parameters are irrelevant to the probability of observing a particular data case(cid:2) This paper shows how such irrelevancies can be exploited to speedup vari(cid:1) ous algorithms for parameter learning in Bayesian networks(cid:2)

N. Zhang

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