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A novel fraud detection system that combines gradient boosting ensembles (LightGBM, XGBoost, CatBoost) with adaptive threshold mechanisms and uncertainty calibration. Unlike fixed-threshold approaches, this system learns optimal operating points per transaction segment using conformal prediction and meta-learning, treating threshold selection as a

Language · Python
License · MIT
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