Relational fuzzy c-lines derived from kernel fuzzy c-lines

研究成果: Conference contribution

抄録

In this paper, three linear fuzzy clustering algorithms are proposed for relational data based on kernel fuzzy c-means, in which the prototypes of clusters are given by lines spanned in a feature space denned by the kernel which derived from a given relational data. The proposed algorithms contrast the conventional method in which the prototypes of clusters are given by lines spanned by two representative objects. Through numerical examples, it is shown that the proposed algorithms can capture local sub-structures in relational data.

本文言語English
ホスト出版物のタイトル6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012
ページ1561-1566
ページ数6
DOI
出版ステータスPublished - 2012 12 1
イベント2012 Joint 6th International Conference on Soft Computing and Intelligent Systems, SCIS 2012 and 13th International Symposium on Advanced Intelligence Systems, ISIS 2012 - Kobe, Japan
継続期間: 2012 11 202012 11 24

出版物シリーズ

名前6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012

Conference

Conference2012 Joint 6th International Conference on Soft Computing and Intelligent Systems, SCIS 2012 and 13th International Symposium on Advanced Intelligence Systems, ISIS 2012
国/地域Japan
CityKobe
Period12/11/2012/11/24

ASJC Scopus subject areas

  • 人工知能
  • ソフトウェア

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