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

Yuchi Kanzawa, Yasunori Endo, Sadaaki Miyamoto

Research output: Chapter in Book/Report/Conference proceedingConference 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 languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages268-281
Number of pages14
Volume5861 LNAI
DOIs
Publication statusPublished - 2009
Event6th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2009 - Awaji Island
Duration: 2009 Nov 302009 Dec 2

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5861 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other6th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2009
CityAwaji Island
Period09/11/3009/12/2

Fingerprint

Clustering algorithms
Entropy
Agglomeration

Keywords

  • Fuzzy c-means
  • Pairwise constraints
  • Semi-supervised clustering

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Kanzawa, Y., Endo, Y., & Miyamoto, S. (2009). Some pairwise constrained semi-supervised fuzzy c-means clustering algorithms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5861 LNAI, 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.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5861 LNAI 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 proceedingConference contribution

Kanzawa, Y, Endo, Y & Miyamoto, S 2009, Some pairwise constrained semi-supervised fuzzy c-means clustering algorithms. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 5861 LNAI, 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, 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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5861 LNAI. 2009. p. 268-281. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-04820-3_25
Kanzawa, Yuchi ; Endo, Yasunori ; Miyamoto, Sadaaki. / Some pairwise constrained semi-supervised fuzzy c-means clustering algorithms. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5861 LNAI 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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