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Found 2 papers, 2 papers with code
FPR Estimation for Fraud Detection in the Presence of Class-Conditional Label Noise
We consider the problem of estimating the false-/ true-positive-rate (FPR/TPR) for a binary classification model when there are incorrect labels (label noise) in the validation set.
Fraud Dataset Benchmark and Applications
Standardized datasets and benchmarks have spurred innovations in computer vision, natural language processing, multi-modal and tabular settings.
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