K-means Based Consensus Clustering

Abstract

Consensus clustering, also known as cluster ensemble or clustering aggregation, aims to find a single clustering from multi-source basic clusterings on the same group of data objects. It has been widely recognized that consensus clustering has merits in generating better clusterings, finding bizarre clusters, handling noise, outliers and sample variations, and integrating solutions from multiple distributed sources of data or attributes.