A Novel Entropy-Based Framework for Hybrid Sampling in Imbalanced Learning
Findings indicate that entropy-based hybrid sampling is a promising approach for structured tabular imbalanced classification, while further validation on high-dimensional text and image datasets remains necessary to establish broader generalizability.