Clustering mixed data

descriptionPublicationkeyboard_double_arrow_right Article 20 May 2011 English Publisher:WileyJournal:WIREs Data Mining and Knowledge Discovery, volume 1, pages 352-361 (issn: 1942-4787, eissn: 1942-4795,

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Authors: Lynette A. Hunt; Murray A. Jorgensen;

doi: 10.1002/widm.33

Clustering mixed data

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Abstract

AbstractMixture model clustering proceeds by fitting a finite mixture of multivariate distributions to data, the fitted mixture density then being used to allocate the data to one of the components. Common model formulations assume that either all the attributes are continuous or all the attributes are categorical. In this paper, we consider options for model formulation in the more practical case ofmixed data: multivariate data sets that contain both continuous and categorical attributes. © 2011 John Wiley & Sons, Inc.WIREs Data Mining Knowl Discov2011 1 352–361 DOI: 10.1002/widm.33This article is categorized under:Algorithmic Development > Structure DiscoveryTechnologies > Structure Discovery and Clustering

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University of Waikato
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