… However, the performance of these approaches require significant improvement. … a novel
approach that leverages deep learning techniques to predict the number of defects in software …

… review on the use of the ensemble learning approach for software defect prediction. The review
is … base learners are generated using different machine learning techniques. These base …

… for any industry with high software development costs. In this … approach for software defect
prediction by using soft computing based machine learning techniques which helps to predict …

… and supervised learners from two perspectives (i) the specific learning algorithm and (ii) the
… make suggestions for machine learning-based, software defect prediction for practitioners. …

… based on machine learning to build a defect prediction model… In this paper, through LIME
analysis, heuristic feature … of improving the accuracy of the Just-in-Time defect prediction model…

… non-defective instances than defective instances in the datasets used for software defect
prediction (… In contrast, conventional machine learning algorithms assume that the numbers of …

… machine learning techniques make that prediction. … improving the predictive ability of defect
models, this paper focuses on investigating techniques to explain software defect predictions…

… The aim of this study was to explore AI machine learning techniques to increase the …
developing a web-based software. Here, several AI machine learning methods were trained, tested, …

… The BNER proposed in our previous work belongs to the traditional CRF machine
learning method. In this paper, we propose a deep learning-based bug-specific named entity …

… In this work complex ML algorithms based on deep learning and CNN were implemented.
Process images were recorded as raw data during selective laser sintering using an …