Bayesian partition modelling
Denison DGT., Adams NM., Holmes CC., Hand DJ.
This paper reviews recent ideas in Bayesian classification modelling via partitioning. These methods provide predictive estimates for class assignments using averages of a sample of models generated from the posterior distribution of the model parameters. We discuss modifications to the basic approach more suitable for problems when there are many predictor variables and/or a large training smple. © 2002 Elsevier Science B.V. All rights reserved.