Improving K-Means Through Better Initialization And Normalization

被引：0

作者：

Choudhary, Akanksha ^{[1
]}

Sharma, Prashant ^{[1
]}

Singh, Manoj ^{[1
]}

机构：

[1] Gurukul Inst Engn & Technol, Dept Comp Sci, Kota, Rajasthan, India

来源：

2016 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATIONS AND INFORMATICS (ICACCI) | 2016年

关键词：

Clustering algorithm; k-means; initialization; normalization;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

K-means is still a popular clustering algorithm and active research area. The research is majorly focused at improving efficiency and effectiveness of the method. This paper proposes combined approach of a ranked initialization and normalization of data values with k-means. Three variations of a score based initialization approach is proposed. Experiments are performed on normalized data to prove the superiority of the proposed algorithm.

引用

页码：2415 / 2419

页数：5

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