tabnet

This paper presents a controlled comparison of seven categorical encoding methods on the IEEE-CIS fraud dataset, evaluating accuracy, interpretability, and computational trade-offs with a fixed LightGBM learner, finding that entity embeddings achieve the highest AUC-ROC but no encoder dominates both metrics.