Fuzzy c-Means Algorithms for Data with Tolerance Based on Opposite Criterions

• KANZAWA Yuchi

  Faculty of Engineering, Shibaura Institute of Technology

• ENDO Yasunori

  Faculty of Systems and Information Engineering, University of Tsukuba

• MIYAMOTO Sadaaki

  Faculty of Systems and Information Engineering, University of Tsukuba

Abstract

In this paper, two new clustering algorithms are proposed for the data with some errors. In any of these algorithms, the error is interpreted as one of decision variables-called "tolerance"-of a certain optimization problem like the previously proposed algorithm, but the tolerance is determined based on the opposite criterion to its corresponding previously proposed one. Applying our each algorithm together with its corresponding previously proposed one, a reliability of the clustering result is discussed. Through some numerical experiments, the validity of this paper is discussed.

Journal

• IEICE transactions on fundamentals of electronics, communications and computer sciences

  IEICE transactions on fundamentals of electronics, communications and computer sciences 90 (10), 2194-2202, 2007-10-01

  The Institute of Electronics, Information and Communication Engineers

Keywords

• fuzzy c-means
• clustering
• tolerance
• reliability of the clustering result

Details

• CRID: 1573387452340435328
• NII Article ID: 110007540891
• NII Book ID: AA10826239
• ISSN: 09168508
• Text Lang: en
• Data Source:
  • CiNii Articles