Selective Affinity Propagation Ensemble Clustering

被引:0
|
作者
Lei, Qi [1 ,2 ]
Li, Ting [3 ]
机构
[1] Cent South Univ, Sch Automat, Changsha 410083, Peoples R China
[2] Hubei Key Lab Adv Control & Intelligent Automat C, Wuhan, Peoples R China
[3] Cent South Univ, Changsha 410083, Peoples R China
基金
中国国家自然科学基金;
关键词
ALGORITHM;
D O I
10.1109/ccta.2019.8920564
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
An ensemble clustering algorithm based on affinity propagation clustering (APC) algorithm is proposed in the paper. Different base clustering results are obtained by using APC algorithm under the selected preference parameter. However, some base clusters have little effect on the final clustering result, the "good" base clusters should be selected from all base clusters. Then the diversity and coverage ratio are applied to the judgement of the homogeneity of generated base clusters. Finally, the evidence accumulation clustering (EAC) algorithm is used for obtaining the co-association matrix from the selected base clusters, and generating final the clustering result. Experimental results on two data sets demonstrate that the clustering ensemble based on the refined co-association matrix outperforms some state-of-the-art clustering ensemble schemes.
引用
收藏
页码:889 / 894
页数:6
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