| ACOSampling: An ant colony optimization-based undersampling method for classifying imbalanced DNA microarray data H Yu, J Ni, J Zhao Neurocomputing 101, 309-318, 2013 | 233 | 2013 |
| 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 | 175 | 2016 |
| 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 | 161 | 2018 |
| 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 | 143 | 2019 |
| 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 | 133 | 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 |
| An improved ensemble learning method for classifying high-dimensional and imbalanced biomedicine data H Yu, J Ni IEEE/ACM transactions on computational biology and bioinformatics 11 (4 …, 2014 | 115 | 2014 |
| 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 | 111 | 2015 |
| A modified ant colony optimization algorithm for tumor marker gene selection H Yu, G Gu, H Liu, J Shen, J Zhao Genomics, proteomics & bioinformatics 7 (4), 200-208, 2009 | 108 | 2009 |
| 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 | 103 | 2016 |
| α-Dominance relation and rough sets in interval-valued information systems X Yang, Y Qi, DJ Yu, H Yu, J Yang Information Sciences 294, 334-347, 2015 | 87 | 2015 |
| Fuzzy support vector machine with relative density information for classifying imbalanced data H Yu, C Sun, X Yang, S Zheng, H Zou IEEE transactions on fuzzy systems 27 (12), 2353-2367, 2019 | 84 | 2019 |
| SMOTE-RkNN: A hybrid re-sampling method based on SMOTE and reverse k-nearest neighbors A Zhang, H Yu, Z Huan, X Yang, S Zheng, S Gao Information Sciences 595, 70-88, 2022 | 83 | 2022 |
| Accelerator for supervised neighborhood based attribute reduction Z Jiang, K Liu, X Yang, H Yu, H Fujita, Y Qian International Journal of Approximate Reasoning 119, 122-150, 2020 | 81 | 2020 |
| Grouped SMOTE with noise filtering mechanism for classifying imbalanced data K Cheng, C Zhang, H Yu, X Yang, H Zou, S Gao IEEE Access 7, 170668-170681, 2019 | 71 | 2019 |
| Accelerator for multi-granularity attribute reduction Z Jiang, X Yang, H Yu, D Liu, P Wang, Y Qian Knowledge-Based Systems 177, 145-158, 2019 | 67 | 2019 |
| Mining and integrating reliable decision rules for imbalanced cancer gene expression data sets H Yu, J Ni, Y Dan, S Xu Tsinghua Science and technology 17 (6), 666-673, 2012 | 65 | 2012 |
| Decision-theoretic rough set: a multicost strategy H Dou, X Yang, X Song, H Yu, WZ Wu, J Yang Knowledge-Based Systems 91, 71-83, 2016 | 60 | 2016 |
| Supervised information granulation strategy for attribute reduction K Liu, X Yang, H Yu, H Fujita, X Chen, D Liu International Journal of Machine Learning and Cybernetics 11, 2149-2163, 2020 | 57 | 2020 |
| Recognition of multiple imbalanced cancer types based on DNA microarray data using ensemble classifiers H Yu, S Hong, X Yang, J Ni, Y Dan, B Qin BioMed research international 2013 (1), 239628, 2013 | 57 | 2013 |
Wankou YangAssociate Professor, School of Automation, Southeast UniversityAdresă de e-mail confirmată pe seu.edu.cn