Learning Directed Probabilistic Logical Models Using Ordering-Search
نویسندگان
چکیده
There is an increasing interest in upgrading Bayesian networks to the relational case, resulting in so-called directed probabilistic logical models. In this paper we discuss how to learn non-recursive directed probabilistic logical models from relational data. This problem has already been tackled before by upgrading the structure-search algorithm for learning Bayesian networks. In this paper we propose to upgrade another algorithm, namely ordering-search, since for Bayesian networks this was found to work better than structure-search. We have implemented both algorithms for the formalism Logical Bayesian Networks and are currently working on an experimental comparison of both algorithms.
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