GDSMOTE: A Novel Synthetic Oversampling Method for High-Dimensional Imbalanced Financial Data
Synthetic oversampling methods for dealing with imbalanced classification problems have been widely studied. However, the current synthetic oversampling methods still cannot perform well when facing high-dimensional imbalanced financial data. The failure of distance measurement in high-dimensional s...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
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| Series: | Mathematics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7390/12/24/4036 |
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