Fuzzy Maximum Scatter Difference Discriminant Criterion Based Clustering Algorithm
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    Abstract:

    In this paper, a fuzzy scatter difference discrimininant criterion is presented. Based on this criterion, fuzzy clustering algorithm FMSDC (fuzzy maximum scatter difference discriminant criterion based clustering algorithm) is also presented. The proposed algorithm reduces dimensionality while clustering by iterative optimizing procedure. First, it introduces the fuzzy concept into maximum scatter difference discriminant criterion; then the parameter η in the fuzzy criterion is appropriately determined based on specific principles so that the sensibility aroused by parameter η can be decreased to some extent; At last clustering and reducing dimensionality are realized according to fuzzy membership μik and optional discriminant vector ω, respectively. Experimental results demonstrate the proposed method FMSDC is not only capable of clustering but also robust and capable of reducing dimensionality.

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皋军,王士同.基于模糊最大散度差判别准则的聚类方法.软件学报,2009,20(11):2939-2949

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  • Received:March 03,2008
  • Revised:July 09,2008
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