Fuzzy inference based subjective clustering method

Takayuki Miyazaki, Masafumi Hagiwara

Research output: Contribution to journalConference article

Abstract

In this paper a new subjective clustering method using fuzzy inference is proposed. Changing some parameters interactively, a user can reflect his/her knowledge or intuition for the clustering. The proposed method takes account of both (1)connectivity of data and (2)linearity of the data distribution. In addition, it represents shapes of clusters by membership functions and uses fuzzy reasoning to reflect subjectivity of a user effectively. The proposed method is also effective not only for clustering but also for various kinds purposes such as data analysis, assumption test, modeling, concept formation support systems, etc. The validity of the proposed method is confirmed by computer simulation.

Original languageEnglish
Pages (from-to)2886-2891
Number of pages6
JournalProceedings of the IEEE International Conference on Systems, Man and Cybernetics
Volume3
Publication statusPublished - 1995 Dec 1
EventProceedings of the 1995 IEEE International Conference on Systems, Man and Cybernetics. Part 2 (of 5) - Vancouver, BC, Can
Duration: 1995 Oct 221995 Oct 25

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ASJC Scopus subject areas

  • Control and Systems Engineering
  • Hardware and Architecture

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