A maximizing model of Bezdek-like spherical fuzzy c-means clustering

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

In this study, a maximizing model of Bezdek-type spherical fuzzy c-means clustering is proposed, which is based on the regularization of the maximizing model of spherical hard c-means. Using theoretical analysis and numerical experiments, it is shown that the proposed method is not equivalent to the minimizing model of Bezdek-type spherical fuzzy c-means, because the effect of its fuzzifier parameter is different from that found in conventional methods.

Original languageEnglish
Title of host publicationProceedings of the 2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2482-2488
Number of pages7
ISBN (Electronic)9781479920723
DOIs
Publication statusPublished - 2014 Sep 4
Event2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2014 - Beijing, China
Duration: 2014 Jul 62014 Jul 11

Publication series

NameIEEE International Conference on Fuzzy Systems
ISSN (Print)1098-7584

Conference

Conference2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2014
CountryChina
CityBeijing
Period14/7/614/7/11

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Artificial Intelligence
  • Applied Mathematics

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  • Cite this

    Kanzawa, Y. (2014). A maximizing model of Bezdek-like spherical fuzzy c-means clustering. In Proceedings of the 2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE (pp. 2482-2488). [6891670] (IEEE International Conference on Fuzzy Systems). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/FUZZ-IEEE.2014.6891670