Fuzzy classification function of fuzzy c-means algorithms for data with tolerance

Yuchi Kanzawa, Yasunori Endo, Sadaaki Miyamoto

研究成果: Conference contribution

抄録

In this paper, two fuzzy classification functions of fuzzy c-means for data with tolerance are proposed. First, two clustering algorithms for data with tolerance are introduced. One is based on the standard method and the other is on the entropy-based one. Second, the fuzzy classification function for fuzzy c-means without tolerance is discussed as the solution of a certain optimization problem. Third, two optimization problems are shown so that the solutions are the fuzzy classification function values for fuzzy c-means algorithms with respect to data with tolerance, respectively. Fourth, Karush-Kuhn-Tucker conditions of two objective functions are considered, and two iterative algorithms are proposed for the optimization problems, respectively. Through some numerical examples, the proposed algorithms are discussed.

本文言語English
ホスト出版物のタイトル2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008
ページ1081-1088
ページ数8
DOI
出版ステータスPublished - 2008 11 7
イベント2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008 - Hong Kong, China
継続期間: 2008 6 12008 6 6

出版物シリーズ

名前IEEE International Conference on Fuzzy Systems
ISSN(印刷版)1098-7584

Conference

Conference2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008
国/地域China
CityHong Kong
Period08/6/108/6/6

ASJC Scopus subject areas

  • ソフトウェア
  • 理論的コンピュータサイエンス
  • 人工知能
  • 応用数学

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