Feature selection combining genetic algorithm and Adaboost classifiers
Hassan Chouaib, Oriol Ramos Terrades, Salvatore Tabbone, Florence Cloppet, Nicole Vincent · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · 2008
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.