A hybrid methodology for learning belief networks: BENEDICT Original Research Article

Previous algorithms for the construction of belief networks structures from data are mainly based either on independence criteria or on scoring metrics. The aim of this paper is to present a hybrid methodology that is a combination of these two approaches, which benefits from characteristics of each one, and to develop two operative algorithms based on this methodology. Results of the evaluation of the algorithms on the well-known Alarm network are presented, as well as the algorithms performance issues and some open problems.