Table 4.

Classification results using dataset splitting of 80% for training and 20% for testing.

Model	Accuracy		Recall		Precision		F1-Score		Time (s)
	Train	Test	Train	Test	Train	Test	Train	Test
Ridge	1.00	0.60	1.00	0.61	1.00	0.59	1.00	0.59	67
QDA	0.39	0.40	0.33	0.33	0.28	0.16	0.26	0.23	72
NB	0.45	0.35	0.43	0.38	0.45	0.42	0.43	0.33	29
k-NN	0.46	0.70	0.42	0.68	0.43	0.76	0.42	0.70	94
SVM	1.00	0.70	1.00	0.69	1.00	0.74	1.00	0.71	53
MLP	1.00	0.65	1.00	0.65	1.00	0.65	1.00	0.65	686
RF	0.86	0.75	0.85	0.74	0.87	0.82	0.86	0.75	48
ET	0.73	0.80	0.70	0.79	0.80	0.88	0.70	0.80	69
GBM	1.00	0.85	1.00	0.86	1.00	0.87	1.00	0.85	749
LightGBM	0.91	0.80	0.91	0.79	0.91	0.80	0.91	0.80	171

The best results are in bold.