Some pairwise constrained semi-supervised fuzzy c-means clustering algorithms

Yuchi Kanzawa, Yasunori Endo, Sadaaki Miyamoto

研究成果: Conference contribution

6 被引用数 (Scopus)

抄録

In this paper, some semi-supervised clustering methods are proposed with two types of pair constraints: two data have to be together in the same cluster, and two data have to be in different clusters, which are classified into two types: one is based on the standard fuzzy c-means algorithm and the other is on the entropy regularized one. First, the standard fuzzy c-means and the entropy regularized one are introduced. Second, a pairwise constrained semi-supervised fuzzy c means are introduced, which is derived from pairwise constrained competitive agglomeration. Third, some new optimization problem are proposed, which are derived from adding new loss function of memberships to the original optimization problem, respectively. Last, an iterative algorithm is proposed by solving the optimization problem.

本文言語English
ホスト出版物のタイトルModeling Decisions for Artificial Intelligence - 6th International Conference, MDAI 2009, Proceedings
ページ268-281
ページ数14
DOI
出版ステータスPublished - 2009 12 1
イベント6th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2009 - Awaji Island, Japan
継続期間: 2009 11 302009 12 2

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
5861 LNAI
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Conference

Conference6th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2009
国/地域Japan
CityAwaji Island
Period09/11/3009/12/2

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

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