← Fraud Detection

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BAF – Base

아카이브 평가 12건 · 마지막 적재/변경 2026-10-30

원본 데이터셋 링크 1

평가 기록

과거 수집 기록이며 최신 순위가 아닙니다. 데이터셋 버전·split·실험 조건과 지표 방향이 검증되지 않은 결과는 직접 비교할 수 없습니다. 날짜는 논문 날짜이며 최신 평가일을 뜻하지 않습니다.

표가 화면보다 넓으면 좌우로 스크롤하여 논문과 구현 링크를 확인하세요.

원본 기록 순서 · 순위 미부여
모델	원본 지표·값	논문	구현
LightGBM	Recall @ 1% FPR 25.2%	RIFF: Inducing Rules for Fraud Detection from Decision Trees 2024-08-23	연결 없음
FIGS	Recall @ 1% FPR 21%	RIFF: Inducing Rules for Fraud Detection from Decision Trees 2024-08-23	연결 없음
CART+RIFF	Recall @ 1% FPR 18.4%	RIFF: Inducing Rules for Fraud Detection from Decision Trees 2024-08-23	연결 없음
CART	Recall @ 1% FPR 16%	RIFF: Inducing Rules for Fraud Detection from Decision Trees 2024-08-23	연결 없음
FIGS+RIFF	Recall @ 1% FPR 15.8%	RIFF: Inducing Rules for Fraud Detection from Decision Trees 2024-08-23	연결 없음
FIGU+RIFF	Recall @ 1% FPR 15.5%	RIFF: Inducing Rules for Fraud Detection from Decision Trees 2024-08-23	연결 없음
LightGBM	Recall @ 5% FPR 54.3%	Decoupling Decision-Making in Fraud Prevention through Classifier Calibration for Business Logic Action 2024-01-10	연결 없음
CatBoost	Recall @ 5% FPR 52.4%	Decoupling Decision-Making in Fraud Prevention through Classifier Calibration for Business Logic Action 2024-01-10	연결 없음
LightGBM	Recall @ 5% FPR 51.76%	Exploring Neural Joint Activity in Spiking Neural Networks for Fraud Detection 2024-11-17	코드 1
1D-CSNN	Recall @ 5% FPR 50.35%	Improving Fraud Detection with 1D-Convolutional Spiking Neural Networks Through Bayesian Optimization 2024-11-16	코드 1
MLP–NN	Recall @ 5% FPR 49.6%	Decoupling Decision-Making in Fraud Prevention through Classifier Calibration for Business Logic Action 2024-01-10	연결 없음
1D-CSNN	Recall @ 5% FPR 42.79%	Exploring Neural Joint Activity in Spiking Neural Networks for Fraud Detection 2024-11-17	코드 1