HS-Gen: a hypersphere-constrained generation mechanism to improve synthetic minority oversampling for imbalanced classification
Abstract Mitigating the impact of class-imbalance data on classifiers is a challenging task in machine learning. SMOTE is a well-known method to tackle this task by modifying class distribution and generating synthetic instances. However, most of the SMOTE-based methods focus on the phase of data se...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2022-12-01
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| Series: | Complex & Intelligent Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s40747-022-00938-9 |