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    Huang Chengquan, Wang Shitong, Jiang Yizhang. A New Fuzzy Clustering Algorithm with Entropy Index Constraint[J]. Journal of Computer Research and Development, 2014, 51(9): 2117-2129. DOI: 10.7544/issn1000-1239.2014.20130305
    Citation: Huang Chengquan, Wang Shitong, Jiang Yizhang. A New Fuzzy Clustering Algorithm with Entropy Index Constraint[J]. Journal of Computer Research and Development, 2014, 51(9): 2117-2129. DOI: 10.7544/issn1000-1239.2014.20130305

    A New Fuzzy Clustering Algorithm with Entropy Index Constraint

    • 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
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