Table 2.
100 sampling experiments | |
---|---|
Mean AUC | |
Logistic Regression (LR) | 0,7947 |
Classification Trees (CT) | 0,7858 |
Random Forest (RF) | 0,8086 |
Gradient Boosting (GB) | 0,8101 |
Neural Networks (NNET) | 0,8085 |
100 sampling experiments | |
---|---|
Mean AUC | |
Logistic Regression (LR) | 0,7947 |
Classification Trees (CT) | 0,7858 |
Random Forest (RF) | 0,8086 |
Gradient Boosting (GB) | 0,8101 |
Neural Networks (NNET) | 0,8085 |