A-SMOTE: A New Preprocessing Approach for Highly Imbalanced Datasets by Improving SMOTE
Imbalance learning is a challenging task for most standard machine learning algorithms. The Synthetic Minority Oversampling Technique (SMOTE) is a well-known preprocessing approach for handling imbalanced datasets, where the minority class is oversampled by producing synthetic examples in feature ve...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Atlantis Press
2019-11-01
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| Series: | International Journal of Computational Intelligence Systems |
| Subjects: | |
| Online Access: | https://www.atlantis-press.com/article/125924019/view |