New Physics: Sae Mulli

Table. 2. Table 2

AUC, CA, F1, Precision, Recall scores for classification models.

Model	Target Class	AUC	CA	F1	Precision	Recall
kNN	ALL	0.986	0.955	0.954	0.953	0.955
SVM		0.997	0.971	0.972	0.973	0.971
Random Forest		0.982	0.933	0.919	0.932	0.933
Neural Network		0.997	0.971	0.971	0.971	0.971
Logistic Regression		0.998	0.976	0.976	0.976	0.976
kNN	BLANK	0.999	0.997	0.995	0.991	1
SVM		1	0.998	0.997	1	0.995
Random Forest		1	0.998	0.997	0.995	1
Neural Network		1	0.998	0.996	0.992	1
Logistic Regression		1	0.999	0.999	0.997	1
kNN	FALSE0.985	0.955	0.965	0.957	0.972
SVM		0.997	0.971	0.977	0.982	0.972
Random Forest		0.979	0.933	0.949	0.909	0.992
Neural Network		0.996	0.971	0.977	0.977	0.977
Logistic Regression		0.998	0.976	0.981	0.978	0.983
kNN	TRUE	0.958	0.958	0.755	0.812	0.706
SVM		0.992	0.973	0.859	0.826	0.894
Random Forest		0.95	0.934	0.479	0.899	0.327
Neural Network		0.991	0.973	0.853	0.866	0.841
Logistic Regression		0.994	0.977	0.871	0.889	0.853

New Phys.: Sae Mulli 2023;73:138~149 https://doi.org/10.3938/NPSM.73.138