文献类型：期刊文献

英文题名：Bayesian multidimensional scale clustering based on dirichlet process

作者：Qing, Xiangyun[1]; Wang, Xingyu[1]

机构：[1] College of Information Science and Technology, East China University of Science and Technology, Shanghai 200237, China

年份：2008

起止页码：546

外文期刊名：Proceedings of the 27th Chinese Control Conference, CCC

收录：EI(收录号：20084011616349)

语种：英文

外文关键词：Gaussian distribution - Markov processes - Chains - Monte Carlo methods

摘要：An important reason for doing multidimensional scaling is to cluster the objects which are only given dissimilarlity metrics. A prior number of components could be infinite in a Bayesian mixture model. In this work we apply infinite Gaussian mixture model and present a Bayesian multidimensional scale clustering method based on Dirichlet process. Estimating the parameters of Bayesian multidimensional scaling model is done using Markov chain Monte Carlo. As the method avoids the model selection, it can be used not only for generating low-dimensional coordinates and model-based clustering simultaneously, but also for choosing the number of clusters and performing parameters of components at the same time.