Table 2.

The GCS-Net and other classic machine learning method model's scores.

Model	Accuracy	auc	aupr	f1	Precision	Recall
GCS-Net	0.844	0.807	0.949	0.913	0.840	1
L2 LogisticRegression	0.800	0.751	0.907	0.886	0.833	0.945
RBF support vector machine	0.733	0.628	0.916	0.846	0.804	0.891
Linear support vector machine	0.777	0.743	0.943	0.871	0.829	0.918
Random forest	0.800	0.785	0.946	0.886	0.833	0.945
Decision tree	0.755	0.692	0.893	0.857	0.825	0.891