A clustering algorithm based on natural nearest neighbor

被引：0

作者：

Zhu, Qingsheng ^{[1
]}

Huang, Jinlong ^{[1
]}

Feng, Ji ^{[1
]}

Zhou, Xianlin ^{[1
]}

机构：

[1] Chongqing Key Lab. of Software Theory and Technology, College of Computer Science, Chongqing University, Chongqing

来源：

Journal of Computational Information Systems | 2014年 / 10卷 / 13期

关键词：

Clustering algorithm; Natural nearest neighbor; Parameter-less;

D O I：

10.12733/jcis10521

中图分类号：

学科分类号：

摘要：

The Clustering has been widely used in many areas such as data analysis, pattern recognition, image processing. It is very difficult for most well-known clustering algorithms to select an appropriate parameter when they run on a dataset. In this paper we propose a novel clustering algorithm based on natural nearest neighbor (CB3N). Natural Nearest Neighbor is a new concept of nearest neighbor which adopts a parameter-less algorithm of searching the natural neighbors for each point in a dataset. Our experiments and performance analysis demonstrate that CB3N could not only cluster a dataset without any parameter, but also get better clustering results than other representative clustering algorithms. © 2014 by Binary Information Press

引用

页码：5473 / 5480

页数：7

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