MAHAKIL:Diversity based Oversampling Approach to Alleviate the Class Imbalance Issue in Software Defect Prediction

• Main Authors: Ebo Bennin K., Keung J., Phannachitta P., Monden A., Mensah S.
• Format: Journal
• Published: 2017
• Online Access: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85028936214&origin=inward; http://cmuir.cmu.ac.th/jspui/handle/6653943832/40258
• Institution: Chiang Mai University

IEEE Highly imbalanced data typically make accurate predictions difficult. Unfortunately, software defect datasets tend to have fewer defective modules than non-defective modules. Synthetic oversampling approaches address this concern by creating new minority defective modules to balance the class d...