Skip to Main content Skip to Navigation
Journal articles

Approche de sélection d’attributs pour la classification basée sur l’algorithme RFE-SVM

Résumé : The feature selection for classification is a very active research field in data mining and optimization. Its combinatorial nature requires the development of specific techniques (such as filters, wrappers, genetic algorithms, and so on) or hybrid approaches combining several optimization methods. In this context, the support vector machine recursive feature elimination (SVM-RFE), is distinguished as one of the most effective methods. However, the RFE-SVM algorithm is a greedy method that only hopes to find the best possible combination for classification. To overcome this limitation, we propose an alternative approach with the aim to combine the RFE-SVM algorithm with local search operators based on operational research and artificial intelligence.
Document type :
Journal articles
Complete list of metadata

Cited literature [15 references]  Display  Hide  Download
Contributor : Coordination Episciences Iam Connect in order to contact the contributor
Submitted on : Friday, April 8, 2016 - 4:09:40 PM
Last modification on : Tuesday, March 22, 2022 - 11:35:48 AM
Long-term archiving on: : Monday, November 14, 2016 - 11:26:13 PM


Publisher files allowed on an open archive




Yahya Slimani, Mohamed Amir Essegir, Mouhamadou Lamine Samb, Fodé Camara, Samba Ndiaye. Approche de sélection d’attributs pour la classification basée sur l’algorithme RFE-SVM. Revue Africaine de la Recherche en Informatique et Mathématiques Appliquées, INRIA, 2014, Volume 17 - 2014 - Special issue CARI'12, pp.197-219. ⟨10.46298/arima.1965⟩. ⟨hal-01300055⟩



Record views


Files downloads