计算机工程与应用2013，Vol.49Issue(4)：149-152,4.DOI:10.3778/j.issn.1002-8331.1107-0273
一种基于PSO&PAM的聚类算法
Approach of clustering based on PSO & PAM algorithm
摘要
Abstract
PAM is the first K-medoids algorithm proposed by one of the algorithm is relatively robust, but PAM sensitive to initial value, easily falling into local convergence. PSO algorithm is used to optimize the PAM, a approach of clustering based on PSO and PAM algorithm is proposed, making full use of both PAM and the PSO for the advantages of different issues, to continuously update the PAM clustering center. Through the establishment of cluster validity function based on entropy, the performance of the hybrid clustering algorithm is evaluated, the UCI data test results show that the hybrid clustering method has high accuracy of clustering.关键词
PAM算法/粒子群优化算法/聚类分析/有效性函数Key words
Partitioning Around Medoid(PAM)/Particle Swarm Optimization (PSO)/cluster analysis/validity function分类
信息技术与安全科学引用本文复制引用
黄翔,蔡碧野,孟颖..一种基于PSO&PAM的聚类算法[J].计算机工程与应用,2013,49(4):149-152,4.基金项目
国家自然科学基金(No.10926189,No.10871031) （No.10926189,No.10871031）
湖南省教育厅重点项目(No.10A015). （No.10A015）
