文章基本信息

标题：A Kernel Fuzzy Clustering Algorithm with Generalized Entropy Based on Weighted Sample
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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.