Accéder directement au contenu Accéder directement à la navigation
Article dans une revue

Empirical study of feature selection methods based on individual feature evaluation for classification problems

Abstract : The use of feature selection can improve accuracy, efficiency, applicability and understandability of a learning process and its resulting model. For this reason, many methods of automatic feature selection have been developed. By using a modularization of feature selection process, this paper evaluates a wide spectrum of these methods. The methods considered are created by combination of different selection criteria and individual feature evaluation modules. These methods are commonly used because of their low running time. After carrying out a thorough empirical study the most interesting methods are identified and some recommendations about which feature selection method should be used under different conditions are provided
Liste complète des métadonnées

https://hal-mines-paristech.archives-ouvertes.fr/hal-00614451
Contributeur : Magalie Prudon <>
Soumis le : jeudi 11 août 2011 - 14:30:57
Dernière modification le : jeudi 24 septembre 2020 - 17:22:03

Identifiants

Citation

Antonio Arauzo-Azofra, José-Luis Aznarte, José-M. Benitez. Empirical study of feature selection methods based on individual feature evaluation for classification problems. Expert Systems with Applications, Elsevier, 2011, 38 (7), pp.Pages 8170-8177. ⟨10.1016/j.eswa.2010.12.160⟩. ⟨hal-00614451⟩

Partager

Métriques

Consultations de la notice

213