Unsupervised feature selection and class labeling for credit card fraud
Abstract Large datasets frequently lack class labels, and obtaining labeled data often involves substantial financial and time costs, along with risks of label noise and inaccuracies due to manual annotation. In the context of fraud detection, such as credit card fraud, these challenges are compound...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-05-01
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| Series: | Journal of Big Data |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40537-025-01154-1 |
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