Clustering Ensemble Approaches: An Overview
聚类融合方法综述

Ensemble approaches are widely and successfully used in classification algorithms and regression models.It can offer better results for overcoming instabilities in classification algorithms and regression models.However,in unsupervised learning,the researches of ensemble approaches are concerned only in recent years.Because the prior information of data sets in unsupervised learning is unknown,the ensemble approaches of classification algorithms and regression models can't be utilized in the same way directly.Recent researches and experiments show that clustering ensemble approaches can enhance the robustness and stabilities of unsupervised learning greatly.This paper makes an overview of the clustering ensemble approaches in recent years.It illustrates the contents and characteristics of recent clustering ensemble approaches research and discusses the future directions of clustering ensemble study.