On FNM-based and RFCM-based fuzzy co-clustering algorithms

Yuchi Kanzawa, Yasunori Endo

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

In this paper, some types of fuzzy co-clustering algorithms are proposed. First, it is shown that the common base of the objective function for quadratic-regularized fuzzy co-clustering and entropy-regularized fuzzy co-clustering is very similar to the base for quadratic-regularized fuzzy nonmetric model and entropy-regularized fuzzy nonmetric model, respectively. Next, it is shown that the above mentioned non-sense clustering problem in previously proposed fuzzy co-clustering algorithms is identical to that in fuzzy nonmetric model algorithms, in the case that all dissimilarities among rows and columns are zero. Based on the above discussion, a method is proposed applying fuzzy nonmetric model after all dissimilarities among rows and columns are non-zero. Furthermore, since relational fuzzy c-means is similar to fuzzy nonmetric model, in the sense that both methods are designed for homogenous relational data, a method is proposed applying relational fuzzy c-means after setting all dissimilarities among rows and columns to some non-zero value. An illustrative numerical example is presented for the proposed methods.

本文言語English
ホスト出版物のタイトル2012 IEEE International Conference on Fuzzy Systems, FUZZ 2012
DOI
出版ステータスPublished - 2012 10 23
イベント2012 IEEE International Conference on Fuzzy Systems, FUZZ 2012 - Brisbane, QLD, Australia
継続期間: 2012 6 102012 6 15

出版物シリーズ

名前IEEE International Conference on Fuzzy Systems
ISSN(印刷版)1098-7584

Conference

Conference2012 IEEE International Conference on Fuzzy Systems, FUZZ 2012
国/地域Australia
CityBrisbane, QLD
Period12/6/1012/6/15

ASJC Scopus subject areas

  • ソフトウェア
  • 理論的コンピュータサイエンス
  • 人工知能
  • 応用数学

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