Fuzzy c-lines for data with tolerance

Yuchi Kanzawa, Yasunori Endo, Sadaaki Miyamoto

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

1 Citation (Scopus)

Abstract

This paper presents a new clustering algorithm, which is based on fuzzy c-lines, can treat data with some errors. First, the tolerance is formulated and introduce into optimization problem of clustering. Next, the problem is solved using Karush-Kuhn-Tucker conditions. Last, the algorithm is constructed based on the results of solving the problem. Some numerical examples for the proposed method are shown.

Original languageEnglish
Title of host publication2009 International Fuzzy Systems Association World Congress and 2009 European Society for Fuzzy Logic and Technology Conference, IFSA-EUSFLAT 2009 - Proceedings
Pages861-866
Number of pages6
Publication statusPublished - 2009 Dec 1
EventJoint 2009 International Fuzzy Systems Association World Congress, IFSA 2009 and 2009 European Society of Fuzzy Logic and Technology Conference, EUSFLAT 2009 - Lisbon, Portugal
Duration: 2009 Jul 202009 Jul 24

Publication series

Name2009 International Fuzzy Systems Association World Congress and 2009 European Society for Fuzzy Logic and Technology Conference, IFSA-EUSFLAT 2009 - Proceedings

Conference

ConferenceJoint 2009 International Fuzzy Systems Association World Congress, IFSA 2009 and 2009 European Society of Fuzzy Logic and Technology Conference, EUSFLAT 2009
CountryPortugal
CityLisbon
Period09/7/2009/7/24

Keywords

  • Data with tolerance
  • Fuzzy c-lines
  • Fuzzy clustering

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Information Systems

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  • Cite this

    Kanzawa, Y., Endo, Y., & Miyamoto, S. (2009). Fuzzy c-lines for data with tolerance. In 2009 International Fuzzy Systems Association World Congress and 2009 European Society for Fuzzy Logic and Technology Conference, IFSA-EUSFLAT 2009 - Proceedings (pp. 861-866). (2009 International Fuzzy Systems Association World Congress and 2009 European Society for Fuzzy Logic and Technology Conference, IFSA-EUSFLAT 2009 - Proceedings).