Fuzzy inference based subjective clustering method

Takayuki Miyazaki, Masafumi Hagiwara

研究成果: Conference article査読

1 被引用数 (Scopus)


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.

ジャーナルProceedings of the IEEE International Conference on Systems, Man and Cybernetics
出版ステータスPublished - 1995 12 1
イベントProceedings of the 1995 IEEE International Conference on Systems, Man and Cybernetics. Part 2 (of 5) - Vancouver, BC, Can
継続期間: 1995 10 221995 10 25

ASJC Scopus subject areas

  • 制御およびシステム工学
  • ハードウェアとアーキテクチャ


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