TABLE 9. The Performance of ML for Testing Result (COVID 19 Dataset).

Feature extraction method	ML Models	Matrix Size	Measure Performance Methods
			Accuracy	Precision	Recall	F1-score
Unigram	DT	3000	95.0	93.71	95.0	94.26
Bi-Gram			94.94	93.64	94.94	94.2
Tri-Gram			94.82	93.49	94.82	94.08
Four-gram			94.82	93.53	94.82	94.1
Unigram	KNN	3000	95.66	92.16	95.66	93.81
Bi-Gram			95.54	92.21	95.54	93.77
Tri-Gram			95.56	92.23	95.56	93.78
Four-gram			95.59	92.36	95.59	93.81
Unigram	RF	3000	96.1	94.95	96.1	94.83
Bi-Gram			96.35	96.07	96.35	95.0
Tri-Gram			96.08	94.89	96.08	94.8
Four-gram			95.97	94.6	95.97	94.73
Unigram	LR	3000	94.73	93.75	94.73	94.19
Bi-Gram			94.83	93.67	94.83	94.18
Tri-Gram			94.77	93.57	94.77	94.1
Four-gram			95.82	94.24	95.82	94.59
Unigram	SVM	3000	96.38	96.18	96.38	95.05
Bi-Gram			96.36	96.09	96.36	95.02
Tri-Gram			96.35	96.07	96.35	95.0
Four-gram			96.35	96.07	96.35	95.0
Unigram	NB	3000	96.06	95.29	96.06	94.37
Bi-Gram			96.12	95.54	96.12	94.51
Tri-Gram			96.13	95.74	96.13	94.5
Four-gram			96.12	95.54	96.12	94.51