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Fraud Detection 벤치마크

Fraud Detection on BAF – Base

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Recall @ 1% FPR

15.5 17.93 20.35 22.77 25.2 2024-08 2026-09 LightGBM — 25.2 (2024-08-23) FIGS — 21.0 (2024-08-23) CART+RIFF — 18.4 (2024-08-23) CART — 16.0 (2024-08-23) FIGS+RIFF — 15.8 (2024-08-23) FIGU+RIFF — 15.5 (2024-08-23) LightGBM — 25.2 (2024-08-23) FIGS — 21.0 (2024-08-23) CART+RIFF — 18.4 (2024-08-23) CART — 16.0 (2024-08-23) FIGS+RIFF — 15.8 (2024-08-23) FIGU+RIFF — 15.5 (2024-08-23) LightGBM — 25.2 (2024-08-23)
RankModel Recall @ 1% FPRRecall @ 5% FPR PaperCodeYear
1 LightGBM 25.2%– RIFF: Inducing Rules for Fraud Detection from Decision Trees 2024
2 FIGS 21%– RIFF: Inducing Rules for Fraud Detection from Decision Trees 2024
3 CART+RIFF 18.4%– RIFF: Inducing Rules for Fraud Detection from Decision Trees 2024
4 CART 16%– RIFF: Inducing Rules for Fraud Detection from Decision Trees 2024
5 FIGS+RIFF 15.8%– RIFF: Inducing Rules for Fraud Detection from Decision Trees 2024
6 FIGU+RIFF 15.5%– RIFF: Inducing Rules for Fraud Detection from Decision Trees 2024
7 LightGBM –54.3% Decoupling Decision-Making in Fraud Prevention through Classifier Calibration for Business Logic Action 2024
8 CatBoost –52.4% Decoupling Decision-Making in Fraud Prevention through Classifier Calibration for Business Logic Action 2024
9 LightGBM –51.76% Exploring Neural Joint Activity in Spiking Neural Networks for Fraud Detection DylanPerdigao/Neural-Joint-Activity-in-SNNs 2024
10 1D-CSNN –50.35% Improving Fraud Detection with 1D-Convolutional Spiking Neural Networks Through Bayesian Optimization DylanPerdigao/Bayesian-Optimization-1D-CSNN 2024
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