Non-Destructive Sample Generation From Conditional Belief Functions

05/25/2020

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by   Mieczysław A. Kłopotek, et al.

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This paper presents a new approach to generate samples from conditional belief functions for a restricted but non trivial subset of conditional belief functions. It assumes the factorization (decomposition) of a belief function along a bayesian network structure. It applies general conditional belief functions.