Entropy regularized fuzzy c-lines for data with tolerance

Yuchi Kanzawa, Yasunori Endo, Sadaaki Miyamoto

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

Abstract

This paper presents a new clustering algorithm ,which is based on entropy regularized 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 IEEE International Conference on Fuzzy Systems - Proceedings
Pages1113-1118
Number of pages6
DOIs
Publication statusPublished - 2009 Dec 10
Event2009 IEEE International Conference on Fuzzy Systems - Jeju Island, Korea, Republic of
Duration: 2009 Aug 202009 Aug 24

Publication series

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

Conference

Conference2009 IEEE International Conference on Fuzzy Systems
CountryKorea, Republic of
CityJeju Island
Period09/8/2009/8/24

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ASJC Scopus subject areas

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

Cite this

Kanzawa, Y., Endo, Y., & Miyamoto, S. (2009). Entropy regularized fuzzy c-lines for data with tolerance. In 2009 IEEE International Conference on Fuzzy Systems - Proceedings (pp. 1113-1118). [5277176] (IEEE International Conference on Fuzzy Systems). https://doi.org/10.1109/FUZZY.2009.5277176