Regularized fuzzy c-means clustering and its behavior at point of infinity

Yuchi Kanzawa, Sadaaki Miyamoto

研究成果: Article

抄録

This study shows that a general regularized fuzzy cmeans (rFCM) clustering algorithm, including some conventional clustering algorithms, can be constructed if a given regularizer function value, its derivative function value, and its inverse derivative function value can be calculated. Furthermore, the results of the study show that the behavior of the fuzzy classification function for rFCM at an infinity point is similar to that for some conventional clustering algorithms.

元の言語English
ページ(範囲)485-492
ページ数8
ジャーナルJournal of Advanced Computational Intelligence and Intelligent Informatics
23
発行部数3
DOI
出版物ステータスPublished - 2019 5 1

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Clustering algorithms
Derivatives
Fuzzy clustering

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

これを引用

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