A Bayesian Method for Constructing Bayesian Belief Networks from Databases
This work addresses the need for automated construction of probabilistic models in applications like hypothesis testing and expert systems, but it appears incremental as it builds on existing Bayesian methods.
The paper tackles the problem of constructing Bayesian belief networks from databases, presenting a Bayesian method and preliminary evaluation results of an algorithm for this task.
This paper presents a Bayesian method for constructing Bayesian belief networks from a database of cases. Potential applications include computer-assisted hypothesis testing, automated scientific discovery, and automated construction of probabilistic expert systems. Results are presented of a preliminary evaluation of an algorithm for constructing a belief network from a database of cases. We relate the methods in this paper to previous work, and we discuss open problems.