Power-regularized fuzzy clustering for spherical data

研究成果: Article

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In this paper, a power-regularization-based fuzzy clustering method is proposed for spherical data. Power regularization has not been previously applied to fuzzy clustering for spherical data. The proposed method is transformed to the conventional fuzzy clustering method, entropy-regularized fuzzy clustering for spherical data (eFCS), for a specified fuzzification parameter value. Numerical experiments on two artificial datasets reveal the properties of the proposed method. Furthermore, numerical experiments on four real datasets indicate that this method is more accurate than the conventional fuzzy clustering methods: standard fuzzy clustering for spherical data (sFCS) and eFCS.

元の言語English
ページ(範囲)163-171
ページ数9
ジャーナルJournal of Advanced Computational Intelligence and Intelligent Informatics
22
発行部数2
DOI
出版物ステータスPublished - 2018 3 1

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ASJC Scopus subject areas

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

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