Name
Abstract | ||
|---|---|---|
The class imbalance problem has posed a leading challenge in real-world applications. Traditional methods focus on either the data level or algorithm level to solve the binary classification problem on imbalanced data, and seldom consider searching an effective transformation for classification. Besides, the undersampling process adopted in them is always subjective and unilateral. To address the ... |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TSMC.2021.3051138 | IEEE Transactions on Systems, Man, and Cybernetics: Systems |
Keywords | DocType | Volume |
Sampling methods,Learning systems,Training,Computers,Boosting,Research and development,Optimized production technology | Journal | 52 |
Issue | ISSN | Citations |
4 | 2168-2216 | 0 |
PageRank | References | Authors |
0.34 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kaixiang Yang | 1 | 4 | 1.38 |
| Zhiwen Yu | 2 | 2753 | 220.67 |
| Yicong Zhou | 3 | 1822 | 108.83 |
| Wen-Ming Cao | 4 | 26 | 11.53 |
| Hau-San Wong | 5 | 1008 | 86.89 |
| jane you | 6 | 123 | 12.02 |
| Guoqiang Han | 7 | 439 | 43.27 |