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  • 标题:A Kernel Fuzzy Clustering Algorithm with Generalized Entropy Based on Weighted Sample
  • 本地全文:下载
  • 作者:Kai Li ; Lijuan Cui
  • 期刊名称:International Journal of Advanced Computer Research
  • 印刷版ISSN:2249-7277
  • 电子版ISSN:2277-7970
  • 出版年度:2014
  • 卷号:4
  • 期号:15
  • 页码:596-600
  • 出版社:Association of Computer Communication Education for National Triumph (ACCENT)
  • 摘要:Aiming at fuzzy clustering with generalized entropy, a kernel fuzzy clustering algorithm with generalized entropy based on weighted sample is presented. By introducing weight of sample into objective function for fuzzy clustering with generalized entropy, we obtain optimization problem for fuzzy clustering with generalized entropy based on weighted sample. And we use Lagrange multiplier method to solve corresponding optimization problem and obtain degree of membership for each sample belonging to different cluster, centers of clusters and weights of samples. Following that, a kernel fuzzy clustering algorithm with generalized entropy based on weighted sample is presented. We select the representative dataset Iris from UCI repository to conduct experiments. Experimental results show the effectiveness of presented algorithm above.
  • 关键词:Fuzzy clustering; generalized entropy; weighted sample; kernel.
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