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JACIII Vol.16 No.1 pp. 174-179
doi: 10.20965/jaciii.2012.p0174
(2012)

Paper:

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On Agglomerative Hierarchical Clustering Using Clusterwise Tolerance Based Pairwise Constraints

Yukihiro Hamasuna*, Yasunori Endo**,
and Sadaaki Miyamoto**

*Department of Informatics, School of Science and Engineering, Kinki University, 3-4-1 Kowakae, Higashi-Osaka, Osaka 577-8502, Japan

**Department of Risk Engineering, Faculty of Systems and Information Engineering, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan

Received:
January 15, 2011
Accepted:
October 3, 2011
Published:
January 20, 2012
Creative Commons License
Keywords:
semi-supervised clustering, agglomerative hierarchical clustering, centroid method, clusterwise tolerance, pairwise constraints
Abstract
This paper presents semi-supervised agglomerative hierarchical clustering algorithm using clusterwise tolerance based pairwise constraints. In semi-supervised clustering, pairwise constraints, that is, must-link and cannot-link, are frequently used in order to improve clustering properties. From that sense, we will propose another way named clusterwise tolerance based pairwise constraints to handle must-link and cannot-link constraints in L2-space. In addition, we will propose semi-supervised agglomerative hierarchical clustering algorithm based on it. We will, moreover, show the effectiveness of the proposed method through numerical examples.
Cite this article as:
Y. Hamasuna, Y. Endo, and S. Miyamoto, “On Agglomerative Hierarchical Clustering Using Clusterwise Tolerance Based Pairwise Constraints,” J. Adv. Comput. Intell. Intell. Inform., Vol.16 No.1, pp. 174-179, 2012.
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