Effect of SMOTE Variants on Software Defect Prediction Classification Based on Boosting Algorithm
Rahmina Ulfah Aflaha, Rudy Herteno, Mohammad Reza Faisal, Friska Abadi, Setyo Wahyu Saputro Abstract Detecting software defects early on is critical for avoiding significant financial losses. However, building accurate software defect prediction models can be challenging due to class imbalance, where the data for defective modules is much less than for standard modules. This research […]