Jul 2026
A Privacy‐Preserving and Explainable Deep Learning Framework for Imbalanced Student Performance Prediction Using CTGAN‐Based Data Augmentation
Identifying high‐performing students in severely imbalanced educational datasets poses significant challenges for conventional machine learning models, which often optimize for overall accuracy while failing to detect extreme minorities. This study proposes a privacy‐preserving and explainable deep learning framework t...
Samira Tajdar, Hakimeh Dustmohammadloo, R. Rakhmonov et al.
· Concurrency and Computation · 0 citations