SMOTE vs. SMOTEENN: A Study on the Performance of Resampling Algorithms for Addressing Class Imbalance in Regression Models
Class imbalance is a prevalent challenge in machine learning that arises from skewed data distributions in one class over another, causing models to prioritize the majority class and underperform on the minority classes. This bias can significantly undermine accurate predictions in real-world scenar...
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| Автори: | , , , , , , |
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| Формат: | Artigo |
| Мова: | Inglês |
| Опубліковано: |
MDPI AG
2025-01-01
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| Серія: | Algorithms |
| Предмети: | |
| Онлайн доступ: | https://www.mdpi.com/1999-4893/18/1/37 |
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