A Method of Two-Stage Clustering with Constraints Using Agglomerative Hierarchical Algorithm and One-Pass k-Means plus

被引：5

作者：

Tamura, Yusuke ^{[1
]}

Obara, Nobuhiro ^{[1
]}

Miyamoto, Sadaaki ^{[2
]}

机构：

[1] Univ Tsukuba, Masters Program Risk Engn, Tsukuba, Ibaraki 3058573, Japan

[2] Univ Tsukuba, Dept Risk Engn, Tsukuba, Ibaraki 3058573, Japan

来源：

KNOWLEDGE AND SYSTEMS ENGINEERING (KSE 2013), VOL 2 | 2014年 / 245卷

关键词：

D O I：

10.1007/978-3-319-02821-7_3

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The aim of this paper is to propose a two-stage method of clustering in which the first stage uses one-pass k-means++ and the second stage uses an agglomerative hierarchical algorithm. This method outperforms a foregoing two-stage algorithm by replacing the ordinary one-pass k-means by one-pass k-means++ in the first stage. Pairwise constraints are also taken into consideration in order to improve its performance. Effectiveness of the proposed method is shown by numerical examples.

引用

页码：9 / 19

页数：11

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