A new efficient validity index for fuzzy clustering

被引：0
|
作者：
Bouguessa, M [1 ]
Wang, SR [1 ]
机构：
[1] Univ Sherbrooke, Dept Comp Sci, Sherbrooke, PQ J1K 2R1, Canada
来源：
PROCEEDINGS OF THE 2004 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7 | 2004年
关键词：
fuzzy clustering; validity indices; overlapping clusters; overlap rate;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A new validity index for fuzzy clustering, which works well in the presence of overlapping clusters that differ in shape, density and orientation, is introduced. A quantitative evaluation of our new validity index in conjunction with seven well-known validity indices is given. For this purpose we use the IRIS data set and generated truthed data sets with prescribed degrees of overlap between clusters. These truthed data sets provide a precise way to evaluate the ability of the validity indices in terms of sensitivity to cluster overlapping.
引用
收藏
页码：1914 / 1919
页数：6
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