title: An evaluation of factors influencing Bayesian learning systems.
abstract: This paper examines the influences of situational and model factors upon the accuracy of Bayesian learning systems. In particular, it is concerned with the impact of variations in training sample size, number of attributes, choice of Bayesian model, and criteria for excluding model attributes upon the overall accuracy of the simple and proper Bayes models.
authors.affiliation: Health Administration Program, Cleveland State University, Ohio 44115.
authors.forename: E L
authors.initials: EL
authors.lastname: Eisenstein
authors.forename: F
authors.initials: F
authors.lastname: Alemi
mesh_terms: D001185:Artificial Intelligence; D001499:Bayes Theorem; D006801:Humans; D007858:Learning; D008491:Medical Informatics Applications; D008962:Models, Theoretical; D011336:Probability; D011379:Prognosis