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基于投票机制的融合聚类算法 被引量：7

Custer Fusion Algorithm Based on Majority Voting Mechanism
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摘要 以一趟聚类算法作为划分数据的基本算法,讨论聚类融合问题.通过重复使用一趟聚类算法划分数据,并随机选择阈值和数据输入顺序,得到不同的聚类结果,将这些聚类结果映射为模式间的关联矩阵,在关联矩阵上使用投票机制获得最终的数据划分.在真实数据集和人造数据集上检验了提出的聚类融合算法,并与相关聚类算法进行了对比,实验结果表明,文中提出的算法是有效可行的. Taking the one-pass clustering algorithm as the basic algorithm for grouping data, the issue of clustering ensemble is investigated. Over multiple clusters obtained by random threshold and sequence of data input of the one-pass clustering algorithm, produces a mapping of the clusters into an association matrix between patterns. The final data partition is obtained by voting mechanism over this association matrix. Experimental results of the proposed cluster fusion algorithm on several real and synthetic data sets are compared with clustering results produced by well known clustering algorithms. The experimental results show that the proposed algorithm is effective and practicable.
作者 蒋盛益
机构地区 广东外语外贸大学信息学院 广东省信息安全技术重点实验室中山大学
出处 《小型微型计算机系统》 CSCD 北大核心 2007年第2期306-309,共4页 Journal of Chinese Computer Systems
基金 国家自然科学基金项目(60503048 60673191)资金 广东外语外贸大学重点项目(GW2005-1-012)资助.
关键词 聚类分析 一趟聚类算法 聚类融合 投票机制 cluster analysis one-pass clustering algorithm cluster fusion voting mechanism
分类号 TP309 [自动化与计算机技术—计算机系统结构]
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参考文献9

  • 1Jiang Sheng-Yi,Xu Yu-Ming.An efficient clustering algorithm[C].In:Proc.of 2004 International Conference on Machine Learning and Cybernetics,2004,8:1513-1518.
  • 2Ana Fred,Anil K Jain.Evidence accumulation clustering based on the K-Means algorithm[Z].SSPR/SPR,Windsor,2002:442-451.
  • 3Alexander P Topchy,Behrouz Minaei-Bidgoli,Anil K Jain,et al.Adaptive clustering ensembles[C].17th International Conference on Pattern Recognition (ICPR'04):2004:272-275.
  • 4Constantinos Boulis,Mari Ostendorf.Combining multiple clustering systems[C].8th European conference on Principles and Practice of Knowledge Discovery in Databases(PKDD),LNAI 3202/2004:63-74.
  • 5Dimitrios Frossyniotis,Minas Pertselakis,Andreas Stafylopatis.A multi-clustering fusion algorithm[C].In:Proc.Of the Second Hellenic Conference on AI,2002:225-236.
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二级参考文献17

  • 1Sudipto Guha, Rajeev Rastogi, Kyuseok Shim. ROCK: A robust clustering algorithm for categorical attributes. In Proc. 1999 Int. Conf. Data Engineering, Sydney, Australia, Mar., 1999, pp.512-521.
  • 2Alexandros Nanopoulos, Yannis Theodoridis, Yannis Manolopoulos. C2P: Clustering based on closest pairs. In Proc. 27th Int. Conf. Very Large Database, Rome, Italy, September, 2001, pp.331-340.
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  • 10Venkatesh Ganti, Johannes Gehrke, Raghu Ramakrishnan. CACTUS-clustering categorical data using summaries.In Proc. 1999 Int. Conf. Knowledge Discovery and Data Mining, August, 1999, pp.73-83.

共引文献31

同被引文献78

引证文献7

二级引证文献15

小型微型计算机系统
2007年 第2期

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