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stat.ML2023★ 2 cited
Generalized Oversampling for Learning from Imbalanced datasets and Associated Theory
Samuel Stocksieker, Denys Pommeret, Arthur Charpentier
In supervised learning, it is quite frequent to be confronted with real imbalanced datasets. This situation leads to a learning difficulty for standard algorithms. Research and sol…
stat.ML2023★ 3 cited
Data Augmentation for Imbalanced Regression
Samuel Stocksieker, Denys Pommeret, Arthur Charpentier
In this work, we consider the problem of imbalanced data in a regression framework when the imbalanced phenomenon concerns continuous or discrete covariates. Such a situation can l…