A Survey: Clustering Ensemble Selection

被引：1

作者：

Min, Liu Li ^{[1
]}

Ping, Fan Xiao ^{[1
]}

机构：

[1] Cent S Univ, Sch Informat Sci & Engn, Changsha, Hunan, Peoples R China

来源：

MEMS, NANO AND SMART SYSTEMS, PTS 1-6 | 2012年 / 403-408卷

关键词：

clustering ensemble; clustering ensemble selection; consensus function; JC; cluster and select; nonnegative matrix factorization;

D O I：

10.4028/www.scientific.net/AMR.403-408.2760

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Traditional clustering ensemble combines all of the available clustering partitions to get the final clustering result. But in supervised classification area,it has been known that selective classifier ensembles can always achieve better solutions. Following the selective classifier ensembles,the question of clustering ensemble is defined as clustering ensemble selection. The paper introduces the concept of clustering ensemble selection and gives the survey of clustering ensemble selection algorithms.

引用

页码：2760 / 2763

页数：4

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