Fuzzy c-Means, its Variants and Generalization, and Their Property from Fuzzy Classification Functions
Author:
Affiliation:
1. School of Information and CommunicKanzawaations Engineering, College of Engineering, Shibaura Institute of Technology
Publisher
Japan Society for Fuzzy Theory and Intelligent Informatics
Link
https://www.jstage.jst.go.jp/article/jsoft/33/2/33_41/_pdf
Reference25 articles.
1. [1] E. H. Ruspini: “A new approach to clustering,” Information and Control, Vol.15, pp. 22-32, 1969.
2. [2] J. C. Dunn: “A Fuzzy Relative of the ISODATA Process and its Use in Detecting Compact Well-Separated Clusters,” J. of Cybernetics, Vol.3, No.3, pp. 32-57, 1973.
3. [3] J. C. Bezdek: “Cluster Validity with Fuzzy Sets,” J. of Cybernetics, Vol.3, No.3, pp. 58-73, 1974.
4. [4] M. P. Windham: “Cluster Validity for the Fuzzy c-Means Clustering Algorithm,” IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol.PAMI-4, No.4, pp. 357-363, 1982.
5. [5] J. C. Bezdek: “Fuzzy mathematics in pattern classification,” Ph.D. dissertation Appl. Math. Cornell Univ., 1973.
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