Improved Algorithm for the k-means Clustering

被引：0

作者：

Zhang, Sheng ^{[1
]}

Wang, Shouqiang ^{[1
]}

机构：

[1] Shandong Jiaotong Univ, Sch Informat Sci & Elect Engn, Jinan, Shandong, Peoples R China

来源：

PROCEEDINGS OF THE 10TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA 2012) | 2012年

关键词：

k-means; clustering; clustering center;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper investigates the standard k-means clustering and gives an improved algorithm based on selecting the initial centers and overcoming the local minimal values. Experiments show that the new algorithm is more effective and can get a better result than the standard k-means clustering.

引用

页码：4717 / 4720

页数：4

共 7 条

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