Synthesizing class labels for highly imbalanced credit card fraud detection data
Abstract Acquiring labeled datasets often incurs substantial costs primarily due to the requirement of expert human intervention to produce accurate and reliable class labels. In the modern data landscape, an overwhelming proportion of newly generated data is unlabeled. This paradigm is especially e...
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| Hlavní autoři: | , , , |
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| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
SpringerOpen
2024-03-01
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| Edice: | Journal of Big Data |
| Témata: | |
| On-line přístup: | https://doi.org/10.1186/s40537-024-00897-7 |
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