Table 2.

Variables’ ranking results. Variables are listed from the most linked to the outcome to the least

Model	AUC	CA	F1	Precision	Recall
Logistic regression	0.914	0.857	0.856	0.859	0.857
Neural network	0.913	0.846	0.845	0.845	0.846
Naïve Bayes	0.909	0.857	0.855	0.860	0.857
Random forest	0.907	0.847	0.846	0.849	0.847
Gradient boosting	0.899	0.844	0.843	0.844	0.844
SVM	0.880	0.849	0.843	0.844	0.844
CN2 rule inducer	0.843	0.774	0.774	0.775	0.774
SGD	0.836	0.849	0.847	0.853	0.849
Tree	0.774	0.786	0.787	0.789	0.786
kNN	0.593	0.589	0.583	0.582	0.589