Enrichment Procedures for Soft Clusters: A Statistical Test and its Applications

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dc.contributor.authorPhillips, Rhonda D.en
dc.contributor.authorWatson, Layne T.en
dc.contributor.authorWynne, Randolph H.en
dc.contributor.authorRamakrishnan, Narenen
dc.contributor.departmentComputer Scienceen
dc.date.accessioned2013-06-19T14:36:00Zen
dc.date.available2013-06-19T14:36:00Zen
dc.date.issued2010-02-01en
dc.description.abstractClusters, typically mined by modeling locality of attribute spaces, are often evaluated for their ability to demonstrate ‘enrichment’ of categorical features. A cluster enrichment procedure evaluates the membership of a cluster for significant representation in pre-defined categories of interest. While classical enrichment procedures assume a hard clustering definition, in this paper we introduce a new statistical test that computes enrichments for soft clusters. We demonstrate an application of this test in refining and evaluating soft clusters for classification of remotely sensed images.en
dc.format.mimetypeapplication/pdfen
dc.identifierhttp://eprints.cs.vt.edu/archive/00001108/en
dc.identifier.sourceurlhttp://eprints.cs.vt.edu/archive/00001108/01/TKDE10.pdfen
dc.identifier.trnumberTR-10-02en
dc.identifier.urihttp://hdl.handle.net/10919/19595en
dc.language.isoenen
dc.publisherDepartment of Computer Science, Virginia Polytechnic Institute & State Universityen
dc.relation.ispartofComputer Science Technical Reportsen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectNumerical analysisen
dc.titleEnrichment Procedures for Soft Clusters: A Statistical Test and its Applicationsen
dc.typeTechnical reporten
dc.type.dcmitypeTexten

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