Boosting random subspace method

The proposed approach is compared with standard AdaBoost and RSM showing an improved performance on a large set of 45 problems from the UCI Machine Learning Repository. An additional study of the effect of noise on the labels of the training instances shows that the less aggressive versions of the proposed methodology are more robust than AdaBoost in the presence of noise.