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dc.contributor.authorBillard, Lynne
dc.contributor.authorDiday, Edwin
dc.date.accessioned2019-09-25T14:23:14Z
dc.date.available2019-09-25T14:23:14Z
dc.date.issued2019
dc.identifier.isbn9780470713938en
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/19921
dc.language.isoenen
dc.subjectsymbolic dataen
dc.subject.ddc519en
dc.titleClustering Methodology for Symbolic Dataen
dc.typeOuvrage
dc.description.abstractenCovers everything readers need to know about clustering methodology for symbolic data—including new methods and headings—while providing a focus on multi-valued list data, interval data and histogram dataThis book presents all of the latest developments in the field of clustering methodology for symbolic data—paying special attention to the classification methodology for multi-valued list, interval-valued and histogram-valued data methodology, along with numerous worked examples. The book also offers an expansive discussion of data management techniques showing how to manage the large complex dataset into more manageable datasets ready for analyses.en
dc.publisher.nameJohn Wiley & Sons, Ltden
dc.subject.ddclabelProbabilités et mathématiques appliquéesen
dc.identifier.citationdate2019-08
dc.relation.forthcomingnonen
dc.description.ssrncandidatenonen
dc.description.halcandidatenonen
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.date.updated2019-09-25T13:54:05Z
hal.person.labIds179320
hal.person.labIds60


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