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arxiv: 1302.4962 · v1 · pith:C2PWWBLTnew · submitted 2013-02-20 · 💻 cs.AI

Cautious Propagation in Bayesian Networks

classification 💻 cs.AI
keywords propagationanalysisbayesianbeencautioushuginwhenaccess
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Consider the situation where some evidence e has been entered to a Bayesian network. When performing conflict analysis, sensitivity analysis, or when answering questions like "What if the finding on X had been y instead of x?" you need probabilities P (e'| h), where e' is a subset of e, and h is a configuration of a (possibly empty) set of variables. Cautious propagation is a modification of HUGIN propagation into a Shafer-Shenoy-like architecture. It is less efficient than HUGIN propagation; however, it provides easy access to P (e'| h) for a great deal of relevant subsets e'.

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