Using SMOTE and Heterogeneous Stacking in Ensemble learning for Software Defect Prediction
Sara Adel El-Shorbagy, Wael El-Gammal, Walid M. Abdelmoez · 2018
Nowadays, there are a lot of classifications models used for predictions in the software engineering field such as effort estimation and defect prediction. One of these models is the ensemble learning machine that improves model performance by combining multiple models in different ways to get a more powerful model.