Distributed Clustering Using Distributed Mixture of Probabilistic PCA

摘要：

　　This paper considers the clustering algorithm based on mixture of probabilistic principle component analyzers in distributed environments.The EM procedure of it is first transformed to a summing variant.Following the classic distributed EM framework for mixture of exponential family distributions and utilizing the summing variant,we propose the distributed EM for mixture of probabilistic principle component analyzers.The proposed algorithm avoids transferring all data from distributed nodes to a central node.Experiment verifies the validity and feasibility of the proposed method.For some datasets,the proposed method can even enhance the log-likelihood as well as the clustering performance.

关键词： Mixture of Probabilistic PCA Distributed Clustering Distributed EM Distributed Data Mining

作者: Hang Yin Chunhong Zhang Yang Ji

作者单位: School of Information and Communication Engineering,Beijing University of Posts and Telecommunications,Beijing,China

会议类型: 国际会议

会议名称: The 2014 10th International Conference on Natural Computation (ICNC 2014) and the 2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2014)(第十届自然计算和第十一届模糊系统与知识发现国际会议)

会议地点: 厦门

会议语种:英文

页码: 360-365

在线出版日期: 2014-08-19（万方平台首次上网日期，不代表论文的发表时间）