Generalization of Tsallis Entropy-Based Fuzzy c-Means Clustering and its Behavior at the Infinity Point

Yuchi Kanzawa, Sadaaki Miyamoto

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

This study presents a generalized Tsallis entropy-based fuzzy c-means (GTFCM) clustering algorithm. Furthermore, the results of this study show that the behavior of GTFCM, at an infinity point of the fuzzy classification function, is similar to that of some conventional clustering algorithms. This result implies that such behavior is determined by a certain part of the GTFCM objective function.

Original languageEnglish
Pages (from-to)884-892
Number of pages9
JournalJournal of Advanced Computational Intelligence and Intelligent Informatics
Volume26
Issue number6
DOIs
Publication statusPublished - 2022 Nov

Keywords

  • Tsallis entropy-based fuzzy c-means clustering, fuzzy classification function

ASJC Scopus subject areas

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

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