Kernelized fuzzy attribute C-means clustering algorithm

A novel kernelized fuzzy attribute C-means clustering algorithm is proposed in this paper. Since attribute means clustering algorithm is an extension of fuzzy C-means algorithm with weighting exponent m = 2 , and fuzzy attribute C-means clustering is a general type of attribute C-means clustering wi...

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Published in	Fuzzy sets and systems Vol. 159; no. 18; pp. 2428 - 2445
Main Authors	Liu, Jingwei, Xu, Meizhi
Format	Journal Article
Language	English
Published	Amsterdam Elsevier B.V 16.09.2008 Elsevier
Subjects	Applied sciences Attribute means clustering Circuit properties Computer science; control theory; systems Control theory. Systems Digital circuits Electric, optical and optoelectronic circuits Electronic circuits Electronics Exact sciences and technology Fuzzy C-means Fuzzy clustering Information, signal and communications theory Kernelized fuzzy C-means Mathematical methods Miscellaneous System theory Telecommunications and information theory Theoretical computing Fuzzy clustering Fuzzy C-means Kernelized fuzzy C-means Attribute means clustering Kernel function Engineering Experimental result Fuzzy system Information processing Database Fuzzy set Algorithm
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ISSN	0165-0114 1872-6801
DOI	10.1016/j.fss.2008.03.018

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Abstract	A novel kernelized fuzzy attribute C-means clustering algorithm is proposed in this paper. Since attribute means clustering algorithm is an extension of fuzzy C-means algorithm with weighting exponent m = 2 , and fuzzy attribute C-means clustering is a general type of attribute C-means clustering with weighting exponent m > 1 , we modify the distance in fuzzy attribute C-means clustering algorithm with kernel-induced distance, and obtain kernelized fuzzy attribute C-means clustering algorithm. Kernelized fuzzy attribute C-means clustering algorithm is a natural generalization of kernelized fuzzy C-means algorithm with stable function. Experimental results on standard Iris database and tumor/normal gene chip expression data demonstrate that kernelized fuzzy attribute C-means clustering algorithm with Gaussian radial basis kernel function and Cauchy stable function is more effective and robust than fuzzy C-means, fuzzy attribute C-means clustering and kernelized fuzzy C-means as well.
AbstractList	A novel kernelized fuzzy attribute C-means clustering algorithm is proposed in this paper. Since attribute means clustering algorithm is an extension of fuzzy C-means algorithm with weighting exponent m = 2 , and fuzzy attribute C-means clustering is a general type of attribute C-means clustering with weighting exponent m > 1 , we modify the distance in fuzzy attribute C-means clustering algorithm with kernel-induced distance, and obtain kernelized fuzzy attribute C-means clustering algorithm. Kernelized fuzzy attribute C-means clustering algorithm is a natural generalization of kernelized fuzzy C-means algorithm with stable function. Experimental results on standard Iris database and tumor/normal gene chip expression data demonstrate that kernelized fuzzy attribute C-means clustering algorithm with Gaussian radial basis kernel function and Cauchy stable function is more effective and robust than fuzzy C-means, fuzzy attribute C-means clustering and kernelized fuzzy C-means as well.
Author	Xu, Meizhi Liu, Jingwei
Author_xml	– sequence: 1 givenname: Jingwei surname: Liu fullname: Liu, Jingwei email: jwliu@buaa.edu.cn, liujingwei03@tsinghua.org.cn organization: LMIB and Department of Mathematics, Beijing University of Aeronautics and Astronautics, Beijing 100083, PR China – sequence: 2 givenname: Meizhi surname: Xu fullname: Xu, Meizhi organization: Department of Mathematics, Tsinghua University, Beijing 100084, PR China
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Keywords	Fuzzy clustering Fuzzy C-means Kernelized fuzzy C-means Attribute means clustering Kernel function Engineering Experimental result Fuzzy system Information processing Database Fuzzy set Algorithm
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SubjectTerms	Applied sciences Attribute means clustering Circuit properties Computer science; control theory; systems Control theory. Systems Digital circuits Electric, optical and optoelectronic circuits Electronic circuits Electronics Exact sciences and technology Fuzzy C-means Fuzzy clustering Information, signal and communications theory Kernelized fuzzy C-means Mathematical methods Miscellaneous System theory Telecommunications and information theory Theoretical computing
Title	Kernelized fuzzy attribute C-means clustering algorithm
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