The use of generative adversarial networks to alleviate class imbalance in tabular data: a survey
Abstract The existence of class imbalance in a dataset can greatly bias the classifier towards majority classification. This discrepancy can pose a serious problem for deep learning models, which require copious and diverse amounts of data to learn patterns and output classifications. Traditionally,...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2022-08-01
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| Series: | Journal of Big Data |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40537-022-00648-6 |