Jhonatan Esquivel

Comparative Evaluation of Synthetic Data Generation Methods for Binary Classification Problems with Class Imbalance

Class imbalance is a critical challenge in the classification of tabular data, since it affects the diagnostic capacity of models in domains such as health and finance. This research compares four synthetic data generation paradigms: traditional interpolation (SMOTE-NC), deep generative models (CTGAN and TVAE), and a h...