Improvement Study and Application Based on K-Means Clustering Algorithm

被引：0
|
作者：
Luo, Yu [1 ]
Yu, Li [2 ]
Liu, Xing-hua [1 ]
机构：
[1] Chongqing Univ Sci & Technol, Sch Elect & Informat Engn, Chongqing 401331, Peoples R China
[2] China Unicom, Chongqing Branch, Chongqing 400040, Peoples R China
来源：
FUZZY INFORMATION AND ENGINEERING, VOLUME 2 | 2009年 / 62卷
关键词：
Data mining; cluster-analysis; k-means; INTUITIONISTIC FUZZY-SETS;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The k-means algorithm is the most classic cluster algorithm based on the distance in the Cluster-analysis. Because of the shortcomings of the traditional k-means algorithm, this paper proposes an improved k-means algorithm which is researched and analyzed. The results, putting into this improved algorithm to analyze the data. of a shopping mall, prove that the algorithm can improve the duality of cluster algorithm and attain a rather good result.
引用
收藏
页码：937 / +
页数：3
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