The proposed Center Initialization Based on Imperialist Competitive Algorithm (CIB-ICA)

被引:0
|
作者
Asfia, Sanaz [1 ]
Delavar, Arash Ghorbannia [1 ]
机构
[1] Payame Noor Univ, Dept Comp, Tehran, Iran
来源
关键词
data mining; clustering; Imperialist Competitive Algorithm; K-means; center initialization;
D O I
10.22436/jmcs.010.04.08
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
In this paper we will introduce an initial cluster centers method for k-means algorithm, which can achieve a significant impact on the convergence and will not fall local optimal solution trap. The proposed Center Initialization Based on Imperialist Competitive Algorithm (CIB-ICA) uses imperialist competitive algorithm and minimum spanning tree(MST) features to reduce clustering error percentage of K-means algorithm. The proposed method has been evaluated on some famous datasets and experimental results show that it is an efficient cluster center initialization method.
引用
收藏
页码:297 / 310
页数:14
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