… use of the ensemble learning approach for software defect … the use of ensemble learning for
software defect prediction are … advances in ensemble learning for software defect prediction …

… the performance of defect classification and to propose an ensemble learning algorithm which
… a novel ensemble learning algorithm to address the issue of software defect classification …

… defect data to predict the defect proneness of new software … of software defect data, which
consists of only a few defective … have been used to predict software defect, almost take no …

… learning and ensemble learning. We thus propose a multiple kernel ensemble learning (MKEL)
approach for software defect … Considering the cost of risk in software defect prediction, …

… In the research background of software defect prediction, this paper explored the optimization
and impacts of ensemble learning on defect classification and built a software defect …

… software defect prediction; this section highlights research work involving defect prediction,
feature selection, ensemble … machine learning methods that can be used for defect prediction. …

… deep learning phase and two-stage ensemble (TSE) phase. We first use SDAEs to extract
the DPs from the traditional software metrics, and then a novel ensemble learning approach, …

… learning can predict software defects by … ensemble learning technique is proposed for
software defect prediction based on feature selection, k-means clustering, and ensemble learning (…

… In recent years, ensemble learning has been frequently used in SDP. Ensemble learning
can effectively improve the generalization ability of individual learners, but how to increase the …

… defective modules during the development (before testing) stage. This process is known as
“Software Defect … prediction of defective modules using variant based ensemble learning and …