Table 3.

Performance of the classification models for postoperative vault prediction

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.