ISSN 1000-1239 CN 11-1777/TP

Journal of Computer Research and Development ›› 2014, Vol. 51 ›› Issue (9): 2117-2129.doi: 10.7544/issn1000-1239.2014.20130305

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A New Fuzzy Clustering Algorithm with Entropy Index Constraint

Huang Chengquan1,2, Wang Shitong1, Jiang Yizhang1   

  1. 1(School of Digital Media, Jiangnan University, Wuxi, Jiangsu 214122);2(School of Science, Guizhou Minzu Univeristy, Guiyang 550025)
  • Online:2014-09-01

Abstract: The fuzziness index m plays an important role in the clustering result of fuzzy clustering algorithms. In order to avoid the fuzziness index m of the CA (competitive agglomeration) clustering algorithm based on FCM (fuzzy C-means) clustering algorithm framework being forced to fix at the usual value 2, a more universal fuzzy clustering algorithm is proposed. Firstly, a fuzzy clustering algorithm named EIC-FCM (entropy index constraint FCM), which has comparable clustering performance to the classical FCM algorithm, is presented by introducing an entropy index r into constraints with m=1. The successful introducing of entropy index r effectively makes the fuzziness index constraint m>1 transform into entropy index constraint 0

Key words: competitive agglomeration, fuzziness index, entropy index, entropy index constraint, fuzzy clustering

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