Fuzziness measurement of fuzzy sets and its application in cluster validity analysis

Gao, X; Li, J; Tao, D; Li, X

Fuzziness measurement of fuzzy sets and its application in cluster validity analysis

Gao, X Li, J Tao, D

Li, X

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Publication Type:: Journal Article
Citation:: International Journal of Fuzzy Systems, 2007, 9 (4), pp. 188 - 197
Issue Date:: 2007-12-01

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Field	Value	Language
dc.contributor.author	Gao, X	en_US
dc.contributor.author	Li, J	en_US
dc.contributor.author	Tao, D https://orcid.org/0000-0001-7225-5449	en_US
dc.contributor.author	Li, X	en_US
dc.date.issued	2007-12-01	en_US
dc.identifier.citation	International Journal of Fuzzy Systems, 2007, 9 (4), pp. 188 - 197	en_US
dc.identifier.issn	1562-2479	en_US
dc.identifier.uri	http://hdl.handle.net/10453/17373
dc.description.abstract	To measure the fuzziness of fuzzy sets, this paper introduces a distance-based and a fuzzy entropybased measurements. Then these measurements are generalized to measure the fuzziness of fuzzy partition, namely partition fuzziness. According to the relationship between the validity of fuzzy partition and its partition fuzziness, a family of cluster validity functions is proposed based on the modified partition fuzziness. The new cluster validity functions overcome the increasing tendency of the traditional partition fuzziness with the cluster number, which provides an effective analysis methodology for fuzzy cluster validity. The experimental results with different testing data sets illustrate the effectiveness, reliability, sensitivity and applicability of the proposed cluster validity function. © 2007 TFSA.	en_US
dc.relation.ispartof	International Journal of Fuzzy Systems	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Fuzziness measurement of fuzzy sets and its application in cluster validity analysis	en_US
dc.type	Journal Article
utslib.citation.volume	4	en_US
utslib.citation.volume	9	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
utslib.for	0102 Applied Mathematics	en_US
utslib.for	0802 Computation Theory and Mathematics	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access
pubs.issue	4	en_US
pubs.publication-status	Published	en_US
pubs.volume	9	en_US

Abstract:

To measure the fuzziness of fuzzy sets, this paper introduces a distance-based and a fuzzy entropybased measurements. Then these measurements are generalized to measure the fuzziness of fuzzy partition, namely partition fuzziness. According to the relationship between the validity of fuzzy partition and its partition fuzziness, a family of cluster validity functions is proposed based on the modified partition fuzziness. The new cluster validity functions overcome the increasing tendency of the traditional partition fuzziness with the cluster number, which provides an effective analysis methodology for fuzzy cluster validity. The experimental results with different testing data sets illustrate the effectiveness, reliability, sensitivity and applicability of the proposed cluster validity function. © 2007 TFSA.

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http://hdl.handle.net/10453/17373