Boosting of (very) weak learners

J. Ferreira, Artur; Figueiredo, Mário

http://hdl.handle.net/10400.21/17910

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Authors

J. Ferreira, Artur

Figueiredo, Mário

Abstract(s)

In 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.

Keywords

boosting weak learners

URI

http://hdl.handle.net/10400.21/17910

Citation

Ferreira, A., Figueiredo, M. – Boosting of (Very) Weak Learners. In Conference on Telecommunications (ConfTele 2007). Peniche, Portugal: dblp – computer science bibliographyr, 2007. Vol. 1, pp. 593-596