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Sélection de variables en apprentissage d'ordonnancement. évaluation des SVM pondérés
OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. This is an author-deposited version published in : http://oatao.univ-toulouse.fr/ Eprints ID : 15268 Any correspondence concerning this service should be sent to the repository administrator: firstname.lastname@example.org ABSTRACT. To select the most useful and the least redundant features to be used in ranking function to reduce computationaldoi:10.3166/dn.18.1.97-121 fatcat:ju6xfabw5jflhmcb2jnrwwjl4i