Fraud Detection On Amazon Fraud
Métriques
AUC-ROC
Averaged Precision
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | AUC-ROC | Averaged Precision |
|---|---|---|
| pick-and-choose-a-gnn-based-imbalanced | 95.86 | 85.49 |
| lex-gnn-label-exploring-graph-neural-network | 97.91 | 92.18 |
| rlc-gnn-an-improved-deep-architecture-for | 97.48 | - |
| reinforced-neighborhood-selection-guided | 96.19 | - |
| semi-supervised-credit-card-fraud-detection-1 | 97.50 | 89.26 |
| enhancing-graph-neural-network-based-fraud | 89.73 | 82.19 |