On Agglomerative Hierarchical Clustering Using Clusterwise Tolerance Based Pairwise Constraints

被引：2

作者：

Hamasuna, Yukihiro ^{[1
]}

Endo, Yasunori ^{[2
]}

Miyamoto, Sadaaki ^{[2
]}

机构：

[1] Kinki Univ, Sch Sci & Engn, Dept Informat, 3-4-1 Kowakae, Higashiosaka, Osaka 5778502, Japan

[2] Univ Tsukuba, Fac Syst & Informat Engn, Dept Risk Engn, Tsukuba, Ibaraki 3058573, Japan

来源：

JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS | 2012年 / 16卷 / 01期

基金：

日本学术振兴会;

关键词：

semi-supervised clustering; agglomerative hierarchical clustering; centroid method; clusterwise tolerance; pairwise constraints;

D O I：

10.20965/jaciii.2012.p0174

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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 L-2-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.

引用

页码：174 / 179

页数：6

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