Table 21.

Performance of model-based and model-free methods (using selected features) on aggregated data.

Method	acc	sens	spec	ppv	npv	lor	auc
Logistic Regression	0.773	0.430	0.952	0.822	0.762	2.696	0.817
Random Forests	0.705	0.453	0.836	0.591	0.746	1.445	0.774
AdaBoost	0.717	0.558	0.800	0.593	0.776	1.620	0.765
XGBoost	0.745	0.547	0.848	0.653	0.782	1.909	0.781
SVM	0.777	0.512	0.915	0.759	0.782	2.425	0.785
Neural Network	0.661	0.512	0.739	0.506	0.744	1.089
Super Learner	0.729	0.453	0.873	0.650	0.754	1.739