On a maximizing model of spherical Bezdek-type possibilistic c-means and fuzzy multi-medoids clustering

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

4 Citations (Scopus)

Abstract

In this study, two clustering frameworks are proposed based on a maximizing model of spherical Bezdek-type fuzzy clustering are proposed. One using possibilistic c-means, and the other using multi-medoids. In each framework, the basic model and its kernelization are presented, along with an appropriate spectral clustering technique. Kernelization allows the frameworks to capture nonlinear-bordered clusters, while spectral clustering solves their local convergence problems. Numerical examples demonstrate that the proposed frameworks produce good clustering results when an adequate parameter values are selected.

Original languageEnglish
Title of host publicationProceedings - 2014 IEEE International Conference on Granular Computing, GrC 2014
EditorsYasuo Kudo, Shusaku Tsumoto
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages121-126
Number of pages6
ISBN (Electronic)9781479954643
DOIs
Publication statusPublished - 2014 Dec 11
Event2014 IEEE International Conference on Granular Computing, GrC 2014 - Hokkaido, Japan
Duration: 2014 Oct 222014 Oct 24

Publication series

NameProceedings - 2014 IEEE International Conference on Granular Computing, GrC 2014

Conference

Conference2014 IEEE International Conference on Granular Computing, GrC 2014
Country/TerritoryJapan
CityHokkaido
Period14/10/2214/10/24

ASJC Scopus subject areas

  • Computer Science Applications
  • Software

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