Abstract
For many inference tasks in Bayesian networks, computational efforts can be restricted to a relevant part of the network. Researchers have studied the relevance of a network’s variables and parameter probabilities for such tasks as sensitivity analysis and probabilistic inference in general, and identified relevant sets of variables by graphical
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