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SOTA
Fraud Detection
Fraud Detection On Amazon Fraud
Fraud Detection On Amazon Fraud
Metrics
AUC-ROC
Averaged Precision
Results
Performance results of various models on this benchmark
Columns
Model Name
AUC-ROC
Averaged Precision
Paper Title
LEX-GNN
97.91
92.18
LEX-GNN: Label-Exploring Graph Neural Network for Accurate Fraud Detection
GTAN
97.50
89.26
Semi-supervised Credit Card Fraud Detection via Attribute-Driven Graph Representation
RLC-GNN
97.48
-
RLC-GNN: An Improved Deep Architecture for Spatial-Based Graph Neural Network with Application to Fraud Detection
RioGNN
96.19
-
Reinforced Neighborhood Selection Guided Multi-Relational Graph Neural Networks
PC-GNN
95.86
85.49
Pick and Choose: A GNN-based Imbalanced Learning Approach for Fraud Detection
CARE-GNN
89.73
82.19
Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters
0 of 6 row(s) selected.
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