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Gaussian clustering method based on maximum-fuzzy-entropy interpretation

โœ Scribed by Rui-Ping Li; Masao Mukaidono

Publisher
Elsevier Science
Year
1999
Tongue
English
Weight
390 KB
Volume
102
Category
Article
ISSN
0165-0114

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โœฆ Synopsis

A new method of fuzzy clustering is proposed. This is a complete Gaussian membership function derived by means of the maximum-entropy interpretation. Compared to the traditional fuzzy c-means (FCM) method, our approach exhibits the following two advantages: (1) having clearer physical meaning and well-defined mathematical features; (2) having an optimal choice for feature parameter a in theory. Moreover, we also review some existing measures of uncertainty of fuzzy sets, and redefine fuzzy entropy as analogous to probabilistic entropy.

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