Table 1.

Classification results using dataset splitting of 90% for training set and 10% for test set.

Model	Accuracy		Recall		Precision		F1-Score		Time (s)
	Train	Test	Train	Test	Train	Test	Train	Test
Ridge	1.00	0.80	1.00	0.81	1.00	0.88	1.00	0.81	44
QDA	0.36	0.40	0.30	0.33	0.22	0.16	0.24	0.23	42
NB	0.52	0.50	0.52	0.53	0.53	0.68	0.51	0.46	27
k-NN	0.76	0.90	0.75	0.89	0.76	0.92	0.75	0.90	37
SVM	0.97	0.90	0.96	0.89	0.97	0.93	0.97	0.90	31
MLP	0.90	0.90	0.88	0.89	0.91	0.92	0.90	0.90	680
RF	0.64	0.90	0.61	0.89	0.63	0.93	0.62	0.90	150
ET	0.60	0.70	0.55	0.67	0.43	0.55	0.50	0.60	46
GBM	0.99	1.00	0.99	1.00	0.99	1.00	0.99	1.00	97
LightGBM	0.99	1.00	0.99	1.00	0.99	1.00	0.99	1.00	290

The best results are shown in bold.