文章基本信息

标题：Affinity Propagation Algorithm Based on Locality Preserving Projections and Particle Swarm Optimization
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作者：Lele Liu ; Zhiping Zhou ; Jiefeng Wang 等
期刊名称：International Journal of Hybrid Information Technology
印刷版ISSN：1738-9968
出版年度：2016
卷号：9
期号：6
页码：169-178
DOI：10.14257/ijhit.2016.9.6.15
出版社：SERSC
摘要：Affinity propagation algorithm is a new powerful and effective clustering method. One of the major problems in clustering is the determination of the optimal number of clusters. In this paper, the particle swarm optimization algorithm is utilized to cope with this problem by using the parameter p as each particle and Silhouette index as the fitness, which can search for the optimal value of p and determine the optimal number of clusters automatically. Moreover, the problem of information overlap is the main drawback of affinity propagation algorithm in dealing with complex structure or high dimensional data for clustering. Hence the enhanced Locality preserving projections method is proposed to integrate with affinity propagation algorithm to reduce the dimension of the data as a processing step. As the result of experiment shows, the proposed method can simultaneously obtain the optimal number of clusters accurately and improve the clustering accuracy by eliminating the redundant information of the data without losing the internal nonlinear structure
关键词：Affinity propagation clustering (AP); Particle swarm optimization (PSO); ; Dimension reduction; Optimal clustering number; Silhouette