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dc.contributor.authorDesmet, Pierre
dc.date.accessioned2019-09-03T09:40:27Z
dc.date.available2019-09-03T09:40:27Z
dc.date.issued1998
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/19644
dc.language.isofren
dc.subjectreseaux de neurones, machine learning, gradient prix
dc.subject.ddc651en
dc.subject.classificationjelL.L6.L62en
dc.subject.classificationjelL.L1.L10en
dc.subject.classificationjelC.C4.C45en
dc.titlePerformance relative des réseaux statistiques à apprentissage: Application à la relation prix-qualité dans l'automobile
dc.typeCommunication / Conférence
dc.description.abstractenThe design and topology of a Neural network is still an important and difficult task. To solve this problem, new approaches are proposed, and specially a combination of Induction rules with a statistical estimation of the coefficients. This research aims to compare an algorithm of this NSL approach with traditional methods (Regression and classical BP neural net). An application on the price-quality relationship for the English automobile market drive to the conclusion that the claimed superiority of the approach is not validated as, compared to BP Neural net and even linear regression, the performance of the GMDH method is inferior.
dc.subject.ddclabelSystème d'informationen
dc.relation.conftitleRencontres Internationales ACSEG
dc.relation.confdate1998-11
dc.relation.confcityLouvain-la -Neuve
dc.relation.confcountryBELGIUM
dc.relation.forthcomingnonen
dc.description.ssrncandidatenon
dc.description.halcandidatenon
dc.description.readershiprecherche
dc.description.audienceInternational
dc.date.updated2020-09-24T14:47:44Z
hal.person.labIds1032


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