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  • 标题:An Efficient Clustering Technique for Message Passing between Data Points using Affinity Propagation
  • 本地全文:下载
  • 作者:D. NAPOLEON ; G.BASKAR ; S.PAVALAKODI
  • 期刊名称:International Journal on Computer Science and Engineering
  • 印刷版ISSN:2229-5631
  • 电子版ISSN:0975-3397
  • 出版年度:2011
  • 卷号:3
  • 期号:1
  • 页码:8-14
  • 出版社:Engg Journals Publications
  • 摘要:A wide range of clustering algorithms is available in literature and still an open area for researcher�s k-means algorithm is one of the basic and most simple partitioning clustering technique is given by Macqueen in 1967. A new clustering algorithm used in this paper is affinity propagation. The number of cluster k has been supplied by the user and the Affinity propagation found clusters with much lower error than other methods, and it did so in less than one-hundredth the amount of time between data point. In this paper we make analysis on cluster algorithm k-means, efficient k-means, and affinity propagation with colon dataset. And the result of affinity propagation shows much lower error when compare with other algorithm and the average accuracy is good.
  • 关键词:Data Mining; Clustering; k-means; Affinity propagation.
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