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IEICE TRANSACTIONS on Information

Unsupervised Learning Algorithm for Fuzzy Clustering

Kiichi URAHAMA

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Summary :

An adaptive algorithm is presented for fuzzy clustering of data. Partitioning is fuzzified by addition of an entropy term to objective functions. The proposed method produces more convex membership functions than those given by the fuzzy c-means algorithm.

Publication
IEICE TRANSACTIONS on Information Vol.E76-D No.3 pp.390-391
Publication Date
1993/03/25
Publicized
Online ISSN
DOI
Type of Manuscript
LETTER
Category
Bio-Cybernetics

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