The impact of feature reduction techniques on defect prediction models

The study of the impact of eight feature reduction techniques on the performance and the variance in performance of five supervised learning and five unsupervised defect prediction models recommends that practitioners who do not wish to choose a best-performing defect prediction model for their data use a neural network-based feature reduction technique.