Generalized adjusted rand indices for cluster ensembles

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

64 Scopus Citations
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Detail(s)

Original languageEnglish
Pages (from-to)2214-2226
Journal / PublicationPattern Recognition
Volume45
Issue number6
Publication statusPublished - Jun 2012

Abstract

In this paper, Adjusted Rand Index (ARI) is generalized to two new measures based on matrix comparison: (i) Adjusted Rand Index between a similarity matrix and a cluster partition (ARImp), to evaluate the consistency of a set of clustering solutions with their corresponding consensus matrix in a cluster ensemble, and (ii) Adjusted Rand Index between similarity matrices (ARImm), to evaluate the consistency between two similarity matrices. Desirable properties of ARI are preserved in the two new measures, and new properties are discussed. These properties include: (i) detection of uncorrelatedness; (ii) computation of ARImp/ARImm in a distributed environment; and (iii) characterization of the degree of uncertainty of a consensus matrix. All of these properties are investigated from both the perspectives of theoretical analysis and experimental validation. We have also performed a number of experiments to show the usefulness and effectiveness of the two proposed measures in practical applications. © 2011 Elsevier Ltd. All rights reserved.

Research Area(s)

  • Adjusted Rand Index, Cluster ensembles, Clustering evaluation

Citation Format(s)

Generalized adjusted rand indices for cluster ensembles. / Zhang, Shaohong; Wong, Hau-San; Shen, Ying.
In: Pattern Recognition, Vol. 45, No. 6, 06.2012, p. 2214-2226.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review