||Author(s): I. Partalas, G. Tsoumakas, I. Vlahavas.
Title: “Pruning an Ensemble of Classifiers via Reinforcement Learning”.
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Ensemble Pruning, Reinforcement Learning.
Neurocomputing, Elsevier, 72(7-9), pp. 1900-1909, 2009.
Abstract: This paper studies the problem of pruning an ensemble of
classifiers from a Reinforcement Learning perspective. It
contributes a new pruning approach that uses the Q-learning
algorithm in order to approximate an optimal policy of choosing
whether to include or exclude each classifier from the ensemble.
Extensive experimental comparisons of the proposed approach
against state-of-the-art pruning and combination methods show very
promising results. Additionally, we present an extension that
allows the improvement of the solutions returned by the proposed
approach over time, which is very useful in certain