ISSN:
0885-6125
Keywords:
probabilistic networks
;
Bayesian belief networks
;
machine learning
;
induction
Source:
Springer Online Journal Archives 1860-2000
Topics:
Computer Science
Notes:
Abstract 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-assisted 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. Finally, we relate the methods in this paper to previous work, and we discuss open problems.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1023/A:1022649401552
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