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

Yuchi Kanzawa; Yasunori Endo; Sadaaki Miyamoto

doi:10.1007/978-3-642-04820-3_25

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

Yuchi Kanzawa, Yasunori Endo, Sadaaki Miyamoto

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

6 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	Modeling Decisions for Artificial Intelligence - 6th International Conference, MDAI 2009, Proceedings
Pages	268-281
Number of pages	14
DOIs	https://doi.org/10.1007/978-3-642-04820-3_25
Publication status	Published - 2009 Dec 1
Event	6th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2009 - Awaji Island, Japan Duration: 2009 Nov 30 → 2009 Dec 2

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5861 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	6th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2009
Country/Territory	Japan
City	Awaji Island
Period	09/11/30 → 09/12/2

Keywords

Fuzzy c-means
Pairwise constraints
Semi-supervised clustering

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-642-04820-3_25

Cite this

Kanzawa, Y., Endo, Y., & Miyamoto, S. (2009). Some pairwise constrained semi-supervised fuzzy c-means clustering algorithms. In Modeling Decisions for Artificial Intelligence - 6th International Conference, MDAI 2009, Proceedings (pp. 268-281). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5861 LNAI). https://doi.org/10.1007/978-3-642-04820-3_25

Some pairwise constrained semi-supervised fuzzy c-means clustering algorithms. / Kanzawa, Yuchi; Endo, Yasunori; Miyamoto, Sadaaki.

Modeling Decisions for Artificial Intelligence - 6th International Conference, MDAI 2009, Proceedings. 2009. p. 268-281 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5861 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Kanzawa, Y, Endo, Y & Miyamoto, S 2009, Some pairwise constrained semi-supervised fuzzy c-means clustering algorithms. in Modeling Decisions for Artificial Intelligence - 6th International Conference, MDAI 2009, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5861 LNAI, pp. 268-281, 6th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2009, Awaji Island, Japan, 09/11/30. https://doi.org/10.1007/978-3-642-04820-3_25

Kanzawa Y, Endo Y, Miyamoto S. Some pairwise constrained semi-supervised fuzzy c-means clustering algorithms. In Modeling Decisions for Artificial Intelligence - 6th International Conference, MDAI 2009, Proceedings. 2009. p. 268-281. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-04820-3_25

Kanzawa, Yuchi ; Endo, Yasunori ; Miyamoto, Sadaaki. / Some pairwise constrained semi-supervised fuzzy c-means clustering algorithms. Modeling Decisions for Artificial Intelligence - 6th International Conference, MDAI 2009, Proceedings. 2009. pp. 268-281 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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

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