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基于Dirichlet分布有限混合模型的Bayes聚类
引用本文:俞燕,徐勤丰,孙鹏飞.基于Dirichlet分布有限混合模型的Bayes聚类[J].应用数学,2006,19(3):600-605.
作者姓名:俞燕  徐勤丰  孙鹏飞
作者单位:复旦大学统计学系,上海,200433
摘    要:本文基于Dirichlet分布有限混合模型,提出了一种用于成分数据的Bayes聚类方法.采用EM算法获得模型参数的估计,用BIC准则确定类数,用类似于Bayes判别的方法对各观测分类.推导了计算公式,编写出程序.模拟研究结果表明,本文提出的方法有较好的聚类效果.

关 键 词:成分数据  Bayes聚类  Dirichlet分布  有限混合模型  EM算法  BIC准则
文章编号:1001-9847(2006)03-0600-06
收稿时间:2005-12-08
修稿时间:2005年12月8日

Bayesian Clustering Based on Finite Mixture Models of Dirichlet Distribution
YU Yan,XU Qin-feng,SUN Peng-fei.Bayesian Clustering Based on Finite Mixture Models of Dirichlet Distribution[J].Mathematica Applicata,2006,19(3):600-605.
Authors:YU Yan  XU Qin-feng  SUN Peng-fei
Institution:Department of Statistics, Fudan University, shanghai 200433, China
Abstract:Based on finite mixture models,we propose a Bayesian clustering method for compositional data.EM algorithm is adopted to compute the estimates of model parameters,BIC is employed to determine the number of clusters,and an analogue procedure of Bayesian discrimination is used to classify each observation.We also deduce iteration formula and write related program.The simulation study shows that this method works well with acceptable clustering results.
Keywords:Compositional data  Bayesian clustering  Dirichlet distribution  Finite mixture models  EM algorithm  BIC (Bayesian information criterion)  
本文献已被 CNKI 维普 万方数据 等数据库收录!
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