Entropy based annealing approach to fuzzy c-means clustering and its interpolation

Author

Yasuda, Makoto

Author_Institution

Dept. of Electr. & Comput. Eng., Gifu Nat. Coll. of Technol., Motosu, Japan

Volume

1

fYear

2011

fDate

26-28 July 2011

Firstpage

424

Lastpage

428

Abstract

The deterministic annealing (DA) and simulated annealing (SA) methods are well combined as DASA. By regularizing the fuzzy c-means method with the fuzzy entropy, the Fermi-Dirac distribution function, well known in statistical mechanics, is obtained as a membership function, and, while optimizing its parameters by SA, the minimal of the Helmholtz free energy for fuzzy c-means clustering is searched by DA. Since shapes of membership functions obtained by DASA are very rough, it is important to interpolate them. Thus, interpolation is introduced to DASA and shows its effectiveness by a numerical experiment.

Keywords

entropy; fuzzy set theory; interpolation; pattern clustering; simulated annealing; statistical mechanics; DASA; Fermi-Dirac distribution function; deterministic annealing method; entropy based annealing approach; fuzzy c-means clustering method; fuzzy entropy; interpolation; membership function; simulated annealing method; statistical mechanics; Annealing; Distribution functions; Entropy; Interpolation; Simulated annealing; Temperature distribution;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems and Knowledge Discovery (FSKD), 2011 Eighth International Conference on

Conference_Location

Shanghai

Print_ISBN

978-1-61284-180-9

Type

conf

DOI

10.1109/FSKD.2011.6019603

Filename

6019603