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ARImp: A generalized Adjusted Rand Index for cluster ensembles

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

Adjusted Rand Index (ARI) is one of the most popular measure to evaluate the consistency between two partitions of data sets in the areas of pattern recognition. In this paper, ARI is generalized to a new measure, Adjusted Rand Index between a similarity matrix and a cluster partition (ARImp), to evaluate the consistency between a set of clustering solutions (or cluster partitions) and their associated consensus matrix in a cluster ensemble. The generalization property of ARImp from ARI is proved and its preservation of desirable properties of ARI is illustrated with simulated experiments. Also, we show with application experiments on several real data sets that ARImp can serve as a filter to identify the less effective cluster ensemble methods. © 2010 IEEE.
Original languageEnglish
Title of host publicationProceedings - International Conference on Pattern Recognition
Pages778-781
DOIs
Publication statusPublished - 2010
Event2010 20th International Conference on Pattern Recognition, ICPR 2010 - Istanbul, Türkiye
Duration: 23 Aug 201026 Aug 2010

Publication series

Name
ISSN (Print)1051-4651

Conference

Conference2010 20th International Conference on Pattern Recognition, ICPR 2010
PlaceTürkiye
CityIstanbul
Period23/08/1026/08/10

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