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hal.structure.identifierCEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
dc.contributor.authorGettler-Summa, Mireille
dc.date.accessioned2018-06-25T14:05:50Z
dc.date.available2018-06-25T14:05:50Z
dc.date.issued2000
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/17880
dc.language.isoenen
dc.subjectMGS(Marking and Generalization by Symbolic Objects)en
dc.subjectSymbolic Data Analysisen
dc.subjectShannon Entropyen
dc.subjectSymbolic Descriptionen
dc.subjectSymbolic Objecten
dc.subjectDiscrimination Criterionen
dc.subjectArtificial Intelligence Approachen
dc.subject.ddc519en
dc.subject.classificationjelD.D5.D52en
dc.titleMarking and Generalization by Symbolic Objects in the Symbolic Official Data Analysis Softwareen
dc.typeChapitre d'ouvrage
dc.description.abstractenIn this paper we propose an automatic method of generating Symbolic Objects in the following framework: description of a partition by symbolic objects that takes into account two aspects, that may be called homogeneity and discrimination criteria. This method belongs to a family of algorithms named MGS (Marking and Generalization by Symbolic Objects),which may be applied either to Factorial Analysis interpretation, to interpretation of partitions or for summarizing huge databases.en
dc.identifier.citationpages414-422en
dc.relation.ispartoftitleData Analysis, Classification, and Related Methodsen
dc.relation.ispartofeditorKiers, Henk A. L.
dc.relation.ispartofeditorRasson, Jean-Paul
dc.relation.ispartofeditorGroenen, Patrick J. F.
dc.relation.ispartofeditorSchader, Martin
dc.relation.ispartofpublnameSpringeren
dc.relation.ispartofpublcityBerlin- Heidelbergen
dc.relation.ispartofdate2000
dc.relation.ispartofpages428en
dc.subject.ddclabelProbabilités et mathématiques appliquéesen
dc.relation.ispartofisbn978-3-540-67521-1en
dc.relation.forthcomingnonen
dc.description.ssrncandidatenonen
dc.description.halcandidatenonen
dc.description.readershiprechercheen
dc.description.audienceInternationalen
hal.author.functionaut


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