Overlapping-Based Rough Clustering Algorithm

Wang Shen-chao; Miao Duo-qian; Chen Min; Wang Rui-zhi

doi:10.3724/SP.J.1146.2007.00450

Volume 30 Issue 7

Jan. 2011

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Article Navigation > Journal of Electronics & Information Technology > 2008 > 30(7): 1713-1716

Wang Shen-chao, Miao Duo-qian, Chen Min, Wang Rui-zhi . Overlapping-Based Rough Clustering Algorithm[J]. Journal of Electronics & Information Technology, 2008, 30(7): 1713-1716. doi: 10.3724/SP.J.1146.2007.00450

Citation:

Wang Shen-chao, Miao Duo-qian, Chen Min, Wang Rui-zhi . Overlapping-Based Rough Clustering Algorithm[J]. Journal of Electronics & Information Technology, 2008, 30(7): 1713-1716. doi: 10.3724/SP.J.1146.2007.00450

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Overlapping-Based Rough Clustering Algorithm

doi: 10.3724/SP.J.1146.2007.00450

Received Date: 2007-03-26
Rev Recd Date: 2007-08-20
Publish Date: 2008-07-19

Abstract

Abstract

Most of traditional clustering algorithms get a partition of sample set with mutually exclusive classes, while there is no explicit boundary between classes mostly in the real world. Introducing rough set theory into clustering analysis, this paper proposes a kind of overlapping-based rough clustering algorithm called KMMRSC which represents a class with multiple centroids and describes the belongingness of samples with the concepts of upper approximation and lower approximation, thus there is overlapping relationship between classes. Experiments show that the algorithm KMMRSC, which can find non-spherical clusters, outperforms classic k-means.

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References

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