Table 6 Binary Classification Algorithms
From: Investigating the effectiveness of one-class and binary classification for fraud detection
Classifier | AUC | AUPRC |
|---|---|---|
Catboost | 0.9693 | 0.8124 |
Extremely Randomized Trees | 0.9348 | 0.6480 |
Random Forest | 0.9627 | 0.7859 |
XGBoost | 0.9682 | 0.7803 |
Logistic Regression | 0.8600 | 0.2901 |