Close to Reality: Interpretable and Feasible Data Augmentation for Imbalanced Learning

Matheus Camilo da Silva, Gabriel Gustavo Costanzo, Andrea de Lorenzo +1

Many machine learning classification tasks involve imbalanced datasets, which are often subject to over-sampling techniques aimed at improving model performance. However, these tec…