Bayesian partition modelling

被引：28
|
作者：
Denison, DGT [1 ]
Adams, NM [1 ]
Holmes, CC [1 ]
Hand, DJ [1 ]
机构：
[1] Univ London Imperial Coll Sci Technol & Med, London SW7 2BU, England
来源：
COMPUTATIONAL STATISTICS & DATA ANALYSIS | 2002年 / 38卷 / 04期
关键词：
Bayesian model averaging; classification; Markov chain Monte Carlo; partitioning;
D O I：
10.1016/S0167-9473(01)00073-1
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
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. (C) 2002 Elsevier Science B.V. All rights reserved.
引用
收藏
页码：475 / 485
页数：11
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