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- Boosting of (very) weak learnersPublication . J. Ferreira, Artur; Figueiredo, MárioIn this paper we apply boosting to weak (binary) learners. The main idea is to combine the output of several simple learners in order to obtain a better classifier. As weak learners we consider generative classifiers and radial basis function classifiers.Our tests on synthetic data show that the proposed algorithm has good convergence properties. On benchmark data, boosting of these weak learners attains results close to the well-known Real AdaBoost algorithm (with decision trees) and support vector machines, constituting a low complexity competitive choice.