Scoring and Searching over Bayesian Networks with Causal and Associative Priors

9 Aug 2014Giorgos BorboudakisIoannis Tsamardinos

A significant theoretical advantage of search-and-score methods for learning Bayesian Networks is that they can accept informative prior beliefs for each possible network, thus complementing the data. In this paper, a method is presented for assigning priors based on beliefs on the presence or absence of certain paths in the true network... (read more)

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