New Inter-Cluster Proximity Index for Fuzzy c-Means Clustering
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概要
- 論文の詳細を見る
This letter presents a new inter-cluster proximity index for fuzzy partitions obtained from the fuzzy c-means algorithm. It is defined as the average proximity of all possible pairs of clusters. The proximity of each pair of clusters is determined by the overlap and the separation of the two clusters. The former is quantified by using concepts of Fuzzy Rough sets theory and the latter by computing the distance between cluster centroids. Experimental results indicate the efficiency of the proposed index.
- （社）電子情報通信学会の論文
- 2008-02-01
著者
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Li Fan
The School Of Computer Science And Engineering University Of Electronic Science And Technology Of Ch
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DAI Shijin
the School of Communication and Information Engineering, University of Electronic Science and Techno
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LIU Qihe
the School of Computer Science and Engineering, University of Electronic Science and Technology of C
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YANG Guowei
the School of Computer Science and Engineering, University of Electronic Science and Technology of C
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Yang Guowei
The School Of Computer Science And Engineering University Of Electronic Science And Technology Of Ch
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Dai Shijin
The School Of Communication And Information Engineering University Of Electronic Science And Technol
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Liu Qihe
The School Of Computer Science And Engineering University Of Electronic Science And Technology Of Ch