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
收藏
页码：9 / 19
页数：11
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