| A novel ensemble method for classifying imbalanced data Z Sun, Q Song, X Zhu, H Sun, B Xu, Y Zhou Pattern Recognition 48 (5), 1623-1637, 2015 | 511 | 2015 |
| Using coding-based ensemble learning to improve software defect prediction Z Sun, Q Song, X Zhu IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and …, 2012 | 234 | 2012 |
| Does bug prediction support human developers? findings from a google case study C Lewis, Z Lin, C Sadowski, X Zhu, R Ou, EJ Whitehead 2013 35th International Conference on Software Engineering (ICSE), 372-381, 2013 | 210 | 2013 |
| A new unsupervised feature selection algorithm using similarity‐based feature clustering X Zhu, Y Wang, Y Li, Y Tan, G Wang, Q Song Computational Intelligence 35 (1), 2-22, 2019 | 62 | 2019 |
| SETE: sequence-based ensemble learning approach for TCR epitope binding prediction Y Tong, J Wang, T Zheng, X Zhang, X Xiao, X Zhu, X Lai, X Liu Computational biology and chemistry 87, 107281, 2020 | 61 | 2020 |
| A selective detector ensemble for concept drift detection L Du, Q Song, L Zhu, X Zhu The Computer Journal 58 (3), 457-471, 2015 | 56 | 2015 |
| Collaborative filtering based recommendation of sampling methods for software defect prediction Z Sun, J Zhang, H Sun, X Zhu Applied Soft Computing 90, 106163, 2020 | 54 | 2020 |
| Dynamic ensemble learning for multi-label classification X Zhu, J Li, J Ren, J Wang, G Wang Information Sciences 623, 94-111, 2023 | 53 | 2023 |
| Ensemble of ML-KNN for classification algorithm recommendation X Zhu, C Ying, J Wang, J Li, X Lai, G Wang Knowledge-Based Systems 221, 106933, 2021 | 38 | 2021 |
| A new classification algorithm recommendation method based on link prediction X Zhu, X Yang, C Ying, G Wang Knowledge-Based Systems 159, 171-185, 2018 | 35 | 2018 |
| An improved data characterization method and its application in classification algorithm recommendation G Wang, Q Song, X Zhu Applied Intelligence 43, 892-912, 2015 | 31 | 2015 |
| An empirical analysis of the FixCache algorithm C Sadowski, C Lewis, Z Lin, X Zhu, EJ Whitehead Jr Proceedings of the 8th Working Conference on Mining Software Repositories …, 2011 | 21 | 2011 |
| A machine learning based software process model recommendation method Q Song, X Zhu, G Wang, H Sun, H Jiang, C Xue, B Xu, W Song Journal of Systems and Software 118, 85-100, 2016 | 20 | 2016 |
| Software change‐proneness prediction through combination of bagging and resampling methods X Zhu, Y He, L Cheng, X Jia, L Zhu Journal of Software: Evolution and Process 30 (12), e2111, 2018 | 18 | 2018 |
| Residuals based EWMA control charts with risk adjustments for zero‐inflated Poisson models X Lai, R Liu, L Liu, J Wang, X Zhang, X Zhu, KC Chong Quality and Reliability Engineering International 38 (1), 283-303, 2022 | 17 | 2022 |
| A risk-adjusted approach to monitoring surgery for survival outcomes based on a weighted score test X Lai, X Li, L Liu, F Tsung, PBS Lai, J Wang, X Zhang, X Zhu, J Liu Computers & Industrial Engineering 160, 107568, 2021 | 16 | 2021 |
| Predicting bugs in software code changes using isolation forest Y He, X Zhu, G Wang, H Sun, Y Wang 2017 IEEE International Conference on Software Quality, Reliability and …, 2017 | 15 | 2017 |
| Automatic recommendation of a distance measure for clustering algorithms X Zhu, Y Li, J Wang, T Zheng, J Fu ACM Transactions on Knowledge Discovery from Data (TKDD) 15 (1), 1-22, 2020 | 14 | 2020 |
| An analysis of programming language statement frequency in C, C++, and Java source code X Zhu, EJ Whitehead Jr, C Sadowski, Q Song Software: practice and experience 45 (11), 1479-1495, 2015 | 14 | 2015 |
| TMBcat: A multi-endpoint p-value criterion on different discrepancy metrics for superiorly inferring tumor mutation burden thresholds Y Wang, X Lai, J Wang, Y Xu, X Zhang, X Zhu, Y Liu, Y Shao, L Zhang, ... Frontiers in Immunology 13, 995180, 2022 | 12 | 2022 |
