ABSTRACT

The popularity of predictive Bayesian networks for supervised classification lies in the combination of generally good predictive accuracy with simplicity and computational efficiency, which is a combination that frequently compares favorably with what is offered by alternatives such as regression models and classification tree learners, such as C4.5 (Quinlan, 1993), at least for many simpler classification problems (for a very brief introduction to classification trees see §7.8).