Bayesian partition modelling

Authors:
D. G. T. Denison;N. M. Adams;C. C. Holmes;D. J. Hand
Affiliations:
Imperial College of Science, Technology and Medicine, London SW7 2BU, UK;Imperial College of Science, Technology and Medicine, London SW7 2BU, UK;Imperial College of Science, Technology and Medicine, London SW7 2BU, UK;Imperial College of Science, Technology and Medicine, London SW7 2BU, UK
Venue:
Computational Statistics & Data Analysis - Nonlinear methods and data mining
Year:
2002

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Abstract

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.