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dc.contributor.authorVogts, Kevin
dc.contributor.authorPope, Nigel
dc.date.accessioned2017-05-03T14:39:27Z
dc.date.available2017-05-03T14:39:27Z
dc.date.issued2004
dc.date.modified2010-08-05T07:16:25Z
dc.identifier.urihttp://hdl.handle.net/10072/33307
dc.description.abstractCluster analysis is a technique used to group objects into clusters such that similar objects are grouped together in the same cluster. Early methods were derived from multivariate statistics. Some newer methods are based on rough sets, introduced by Pawlak [3], [4]. An extension of rough sets to rough clusters was introduced in [5]. The lower approximation (LA) of a rough cluster contains objects that only belong to that cluster, and the upper approximation (UA) contains objects that may belong to more than one cluster. An EA can be used to find a set of lower approximations of rough clusters that provide the most comprehensive coverage of the data set with the minimum number of clusters.
dc.description.publicationstatusYes
dc.languageEnglish
dc.language.isoeng
dc.publisherSpringer
dc.publisher.placeUSA
dc.publisher.urihttp://www.sigevo.org/gecco-2004/
dc.relation.ispartofconferencenameGenetic and Evolutionary Computation • GECCO 2004
dc.relation.ispartofconferencetitleGenetic and Evolutionary Computation Conference Seattle,WA, USA, June 26-30, 2004 Proceedings, Part II
dc.relation.ispartofdatefrom2004-06-26
dc.relation.ispartofdateto2004-06-30
dc.relation.ispartoflocationSeattle
dc.subject.fieldofresearchMarketing Research Methodology
dc.subject.fieldofresearchcode150505
dc.titleGenerating compact rough cluster descriptions using an evolutionary algorithm
dc.typeConference output
dc.type.descriptionE3 - Conferences (Extract Paper)
dc.type.codeE - Conference Publications
gro.date.issued2004
gro.hasfulltextNo Full Text
gro.griffith.authorPope, Nigel K.


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    Contains papers delivered by Griffith authors at national and international conferences.

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