Model | Accuracy (95% CI) | Mean AUC (95% CI) |
Decision Tree | 0.261 (0.232 to 0.290) | 0.637 (0.630 to 0.643) |
Random Forest | 0.828 (0.819 to 0.836) | 0.765 (0.744 to 0.785) |
Adaboost | 0.492 (0.486 to 0.499) | 0.645 (0.629 to 0.661) |
Gradient Boosting | 0.815 (0.809 to 0.821) | 0.718 (0.690 to 0.746) |
XGBoost | 0.802 (0.791 to 0.813) | 0.733 (0.707 to 0.759) |
SVC | 0.497 (0.494 to 0.499) | 0.705 (0.690 to 0.721) |
AUC, area under the curve; SVC, Support Vector Classification.