A Bayesian method for the induction of probabilistic networks from data. (English) Zbl 0766.68109

Cooper, Gregory F.; Herskovits, Edward

Mach. Learn. 9, No. 4, 309-347 (1992).

Summary: This paper presents a Bayesian method for constructing probabilistic networks from databases. In particular, we focus on constructing Bayesian belief networks. Potential applications include computer-associated hypothesis testing, automated scientific discovery, and automated construction of probabilistic expert systems. We extend the basic method to handle missing data and hidden (latent) variables. We show how to perform probabilistic inference by averaging over the inferences of multiple belief networks. Results are presented of a preliminary evaluation of an algorithm for constructing a belief network from a database of cases.

MSC:

68T05

Learning and adaptive systems in artificial intelligence

Keywords:

machine learning; induction; probabilistic networks; Bayesian belief networks