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.
A hybrid feature selection with ensemble classification for imbalanced healthcare data: A case study for brain tumor diagnosis.IEEE Access, 4:9145– 9154, 2016
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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.