On Linear Clustering with Constraints on Cluster Size

被引：0

作者：

Kimoto, Naoya ^{[1
]}

Endo, Yasunori ^{[2
]}

机构：

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

[2] Univ Tsukuba, Fac Engn Informat & Syst, 1-1-1 Tennodai, Tsukuba, Ibaraki 3058573, Japan

来源：

2018 JOINT 10TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND INTELLIGENT SYSTEMS (SCIS) AND 19TH INTERNATIONAL SYMPOSIUM ON ADVANCED INTELLIGENT SYSTEMS (ISIS) | 2018年

关键词：

clustering; linear structure; constraints on cluster size;

D O I：

10.1109/SCIS-ISIS.2018.00137

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Clustering is unsupervised classification method m the field of machine learning. e-varieties (CV) and c-regression (CR) are linear clustering that can find linear structures of a dataset. CV and CR are clustering algorithms that perform principal component analysis and regression analysis at the same time, respectively. By the way, when clustering is used in the actual society, there are situations when_ the number of objects in each cluster is restricted. In this paper, we propose new linear clustering algorithms with constraints on cluster size.

引用

页码：832 / 836

页数：5

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