| Dominance-based rough set approach and knowledge reductions in incomplete ordered information system X Yang, J Yang, C Wu, D Yu Information Sciences 178 (4), 1219-1234, 2008 | 269 | 2008 |
| A comparative study of multigranulation rough sets and concept lattices via rule acquisition J Li, Y Ren, C Mei, Y Qian, X Yang Knowledge-Based Systems 91, 152-164, 2016 | 183 | 2016 |
| Dominance-based rough set approach to incomplete interval-valued information system X Yang, D Yu, J Yang, L Wei Data & Knowledge Engineering 68 (11), 1331-1347, 2009 | 178 | 2009 |
| Multi-label learning with label-specific feature reduction S Xu, X Yang, H Yu, DJ Yu, J Yang, ECC Tsang Knowledge-Based Systems 104, 52-61, 2016 | 170 | 2016 |
| Test cost sensitive multigranulation rough set: model and minimal cost selection X Yang, Y Qi, X Song, J Yang Information Sciences 250, 184-199, 2013 | 169 | 2013 |
| Generalization of soft set theory: from crisp to fuzzy case X Yang, D Yu, J Yang, C Wu Fuzzy Information and Engineering: Proceedings of the Second International …, 2007 | 166 | 2007 |
| Active learning from imbalanced data: A solution of online weighted extreme learning machine H Yu, X Yang, S Zheng, C Sun IEEE transactions on neural networks and learning systems 30 (4), 1088-1103, 2018 | 155 | 2018 |
| Neighborhood systems-based rough sets in incomplete information system X Yang, M Zhang, H Dou, J Yang Knowledge-Based Systems 24 (6), 858-867, 2011 | 141 | 2011 |
| Pseudo-label neighborhood rough set: measures and attribute reductions X Yang, S Liang, H Yu, S Gao, Y Qian International journal of approximate reasoning 105, 112-129, 2019 | 136 | 2019 |
| Updating multigranulation rough approximations with increasing of granular structures X Yang, Y Qi, H Yu, X Song, J Yang Knowledge-Based Systems 64, 59-69, 2014 | 131 | 2014 |
| Rough set based semi-supervised feature selection via ensemble selector K Liu, X Yang, H Yu, J Mi, P Wang, X Chen Knowledge-based systems 165, 282-296, 2019 | 125 | 2019 |
| An efficient selector for multi-granularity attribute reduction K Liu, X Yang, H Fujita, D Liu, X Yang, Y Qian Information Sciences 505, 457-472, 2019 | 119 | 2019 |
| Support vector machine-based optimized decision threshold adjustment strategy for classifying imbalanced data H Yu, C Mu, C Sun, W Yang, X Yang, X Zuo Knowledge-Based Systems 76, 67-78, 2015 | 110 | 2015 |
| Multi-granulation rough set: from crisp to fuzzy case XB Yang, XN Song, HL Dou, JY Yang Annals of Fuzzy Mathematics and Informatics 1 (1), 55-70, 2011 | 110 | 2011 |
| Three-way k-means: integrating k-means and three-way decision P Wang, H Shi, X Yang, J Mi International journal of machine learning and cybernetics 10, 2767-2777, 2019 | 101 | 2019 |
| ODOC-ELM: Optimal decision outputs compensation-based extreme learning machine for classifying imbalanced data H Yu, C Sun, X Yang, W Yang, J Shen, Y Qi Knowledge-Based Systems 92, 55-70, 2016 | 101 | 2016 |
| Multigranulation rough sets in incomplete information system X Yang, J Yang, X Yang, J Yang Incomplete information system and rough set theory: models and attribute …, 2012 | 101 | 2012 |
| Ensemble selector for attribute reduction X Yang, Y Yao Applied Soft Computing 70, 1-11, 2018 | 100 | 2018 |
| Constructive and axiomatic approaches to hesitant fuzzy rough set X Yang, X Song, Y Qi, J Yang Soft Computing 18, 1067-1077, 2014 | 94 | 2014 |
| Attribute group for attribute reduction Y Chen, K Liu, J Song, H Fujita, X Yang, Y Qian Information Sciences 535, 64-80, 2020 | 93 | 2020 |
