AER is a dynamic ensemble method that reports improved balanced accuracy on seven UCI imbalanced datasets and five GMM-generated variants, with a theoretical complexity claim that is not correctly proved.
Learning from class-imbalanced data: Review of methods and applications.Expert Systems with Applications, 73:220–239, 2017
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Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification
AER is a dynamic ensemble method that reports improved balanced accuracy on seven UCI imbalanced datasets and five GMM-generated variants, with a theoretical complexity claim that is not correctly proved.