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Ensemble techniques have been widely used for improving the classification accuracy, and recent studies show that ensembling classifiers through multi-modal perturbation can further improve the classification performance. In this paper, we propose a novel selective ensemble algorithm (called SE_AROS) based on approximate reducts and optimal sampling. In SE_AROS, we design a multi-modal perturbation...
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