TabKANet for Software Defect Prediction: An Oversampling and Feature-Selection Ablation Study
This study adapts TabKANet to the all-numerical, highly imbalanced SDP setting and empirically evaluates it against established baselines, using a structured ablation in order to isolate the contribution of oversampling and feature selection rather than to propose a new architecture.
Setyo Wahyu Saputro, M. Faza, Azhiman Saputra Setyo et al.
· 0 citations