| A-SMOTE: A new preprocessing approach for highly imbalanced datasets by improving SMOTE AS Hussein, T Li, CW Yohannese, K Bashir International Journal of Computational Intelligence Systems 12 (2), 1412-1422, 2019 | 61 | 2019 |
| Enhancing software defect prediction using supervised-learning based framework K Bashir, T Li, CW Yohannese, Y Mahama 2017 12th International Conference on Intelligent Systems and Knowledge …, 2017 | 34 | 2017 |
| Enhancing crash injury severity prediction on imbalanced crash data by sampling technique with variable selection M Yahaya, X Jiang, C Fu, K Bashir, W Fan 2019 IEEE Intelligent Transportation Systems Conference (ITSC), 363-368, 2019 | 31 | 2019 |
| Bayesian networks for imbalance data to investigate the contributing factors to fatal injury crashes on the Ghanaian highways M Yahaya, R Guo, W Fan, K Bashir, Y Fan, S Xu, X Jiang Accident Analysis & Prevention 150, 105936, 2021 | 19 | 2021 |
| A three-stage based ensemble learning for improved software fault prediction: an empirical comparative study CW Yohannese, T Li, K Bashir International Journal of Computational Intelligence Systems 11 (1), 1229-1247, 2018 | 16 | 2018 |
| SMOTEFRIS-INFFC: Handling the challenge of borderline and noisy examples in imbalanced learning for software defect prediction K Bashir, T Li, CW Yohannese, M Yahaya Journal of Intelligent & Fuzzy Systems 38 (1), 917-933, 2020 | 13 | 2020 |
| Ensemble-based model selection for imbalanced data to investigate the contributing factors to multiple fatality road crashes in Ghana M Yahaya, R Guo, X Jiang, K Bashir, C Matara, S Xu Accident Analysis & Prevention 151, 105851, 2021 | 12 | 2021 |
| An empirical study for enhanced software defect prediction using a learning-based framework K Bashir, T Li, CW Yohannese International Journal of Computational Intelligence Systems 12 (1), 282-298, 2018 | 11 | 2018 |
| A novel feature selection method based on maximum likelihood logistic regression for imbalanced learning in software defect prediction. K Bashir, T Li, M Yahaya Int. Arab J. Inf. Technol. 17 (5), 721-730, 2020 | 10 | 2020 |
| ASMOTE: a new pre-processing approach for highly imbalanced datasets by improving SMOTE international journal of computational intelligence systems AS Hussein, T Li, CW Yohannese, K Bashir vol 12, 1412, 2019 | 5 | 2019 |
| A hybrid data preprocessing technique based on maximum likelihood logistic regression with filtering for enhancing software defect prediction K Bashir, T Ali, M Yahaya, AS Hussein 2019 IEEE 14th International Conference on Intelligent Systems and Knowledge …, 2019 | 4 | 2019 |
| A modified adaptive synthetic sampling method for learning imbalanced datasets AS Hussein, T Li, DM Abd Ali, K Bashir, CW Yohannese Developments of Artificial Intelligence Technologies in Computation and …, 2020 | 3 | 2020 |
| A novel preprocessing approach for imbalanced learning in software defect prediction K Bashir, T Li, CW Yohannese, M Yahaya, T Ali Data Science and Knowledge Engineering for Sensing Decision Support …, 2018 | 2 | 2018 |
| A Novel Hybrid Approach Based on Rough Set for Classification: An Empirical Comparative Study. AS Hussein, T Li, CW Yohannese, K Bashir Journal of Multiple-Valued Logic & Soft Computing 33, 2019 | 1 | 2019 |
| Software fault prediction using data reduction approaches CW Yohannese, T Li, K Bashir, M Simfukwe, AS Hussein Data Science and Knowledge Engineering for Sensing Decision Support …, 2018 | 1 | 2018 |
| Rotating machine fault detection using operational defection shape (ODS) KED Bashir, ZM Ripin, IF Abd Rahim, SFM Dahlan | | 2007 |
Chubato Wondaferaw YohanneseSouthwest Jiaotong University在 my.swjtu.edu.cn 的电子邮件经过验证
Chubato Wondaferaw YohanneseSouthwest Jiaotong University在 my.swjtu.edu.cn 的电子邮件经过验证