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Fraud Detection

Active Speaker Detection › Fraud Detection 45 평가 기록 12 datasets

Fraud Detection is a vital topic that applies to many industries including the financial sectors, banking, government agencies, insurance, and law enforcement, and more. Fraud endeavors have detected a radical rise in current years, creating this topic more critical than ever. Despite struggles on the part of the troubled organizations, hundreds of millions of dollars are wasted to fraud each year. Because nearly a few samples confirm fraud in a vast community, locating these can be complex. Data mining and statistics help to predict and immediately distinguish fraud and take immediate action to minimize costs.

<span class="description-source">Source: Applying support vector data description for fraud detection </span>

개요는 각 항목의 일부입니다. 위 탭에서 전체 기록을 페이지별로 탐색할 수 있습니다.

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Dataset기록된 모델 예시MetricPaperCode
LightGBM
Recall @ 1% FPR: 25.2%
논문 -
LEX-GNN
AUC-ROC: 96.40Averaged Precision: 83.56F1 Macro: 86.35G-mean: 84.91
논문 코드
LEX-GNN
AUC-ROC: 97.91Averaged Precision: 92.18F1 Macro: 93.48G-mean: 92.03
논문 코드
GCN
AUPRC: 0.5946AUC: 0.8329
논문 코드
BiRank
AUC: 0.786AUPRC: 0.175
논문 코드
DevNet
AUC: 0.98Average Precision: 0.69
논문 코드
1D-CSNN
Recall @ 5% FPR: 40.71%
논문 코드
1D-CSNN
Recall @ 5% FPR: 47.08%
논문 코드
1D-CSNN
Recall @ 5% FPR: 41.83%
논문 코드
1D-CSNN
Recall @ 5% FPR: 35.54%
논문 코드
1D-CSNN
Recall @ 5% FPR: 34.96%
논문 코드
SplitGNN
AUC-ROC: 68.98
논문 코드

데이터셋

12개
BAF – BaseYelp-FraudAmazon-FraudElliptic DatasetHealthcare Provider Fraud Detection AnalysisKaggle-Credit Card Fraud DatasetBAF – Variant IBAF – Variant IIBAF – Variant IIIBAF – Variant IVBAF – Variant VFDCompCN

논문

라이브러리

Papers with Code 리더보드 row에 연결된 구현 저장소입니다.

github.com/DylanPerdigao/Neural-Joint-Activity-in-SNNs 1 논문
github.com/DylanPerdigao/Bayesian-Optimization-1D-CSNN 1 논문