Feature selection combining genetic algorithm and adaboost classifiers

H. Chouaib, Oriol Ramos Terrades, S. Tabbone, F. Cloppet, N. Vincent

Producció científica: Informe/llibreLlibre d'ActesRecercaAvaluat per experts

29 Cites (Scopus)

Resum

This paper presents a fast method using simple genetic algorithms (GAs) for features selection. Unlike traditional approaches using GAs, we have used the combination of Adaboost classifiers to evaluate an individual of the population. So, the fitness function we have used is defined by the error rate of this combination. This approach has been implemented and tested on the MNIST database and the results confirm the effectiveness and the robustness of the proposed approach.
Idioma originalAnglès
Nombre de pàgines4
DOIs
Estat de la publicacióPublicada - 2008

Fingerprint

Navegar pels temes de recerca de 'Feature selection combining genetic algorithm and adaboost classifiers'. Junts formen un fingerprint únic.

Com citar-ho