J4 ›› 2009, Vol. 44 ›› Issue (9): 40-42.

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A clustering algorithm based on feature point selection

 SHU Guo-Gong, DAN Bing, GENG Xiao-Na   

  1. 1. School of Computer Science and Technology, Shandong University, Jinan 250101, Shandong, China;  2. Henan University of Urban Construction, Pingdingshan 467044, Henan, China
  • Received:2009-05-20 Online:2009-09-16 Published:2009-11-05

Abstract:

A clustering algorithm based on Feature Point Selection in Data Mining (abbreviated CFPS) is put forward in this paper. This method can overcome the disadvantage of a algorithm  which requires the number of clusters for numerical incoming data. The CFPS algorithm finds the optimal number of clusters, andgreatly improves the precision and efficiency of clustering. The results of experiments prove that  using the algorithm for the numerical data clustering method is feasible, which is valuable for further study in more depth.

Key words: clustering; k means; data mining

CLC Number: 

  • TP311
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