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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
arima:1965 - Revue Africaine de Recherche en Informatique et Mathématiques Appliquées, 18 août 2014, Volume 17 - 2014 - Numéro spécial - CARI'12 - https://doi.org/10.46298/arima.1965- 1 Ecole Supérieure de Technologie et d'Informatique [Tunis-Carthage]
- 2 Laboratoire de Génie Informatique et d'Automatique de l'Artois
- 3 département Mathématiques Informatique
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.