Effective Utilization of Data for Predicting COVID-19 Dynamics: An Exploration through Machine Learning Models

Table 13

MAE values of support vector regression models for confirmed cases.

Forecast period (days)	Cumulative cases				Daily cases
	Germany	Japan	South Korea	Ukraine	Germany	Japan	South Korea	Ukraine
Train 3	177461.93	42413.24	345269.25	6168.6	21543.02	6972.67	12801.19	1318.78
Test 3	29971.42	72498.7	31604.26	14735.92	9307.22	20931.64	11677.88	2895.02
Train 7	265493.7	77343.36	611024.82	11372.04	23277.99	9217.39	15721.31	1711.46
Test 7	18319.71	67374.52	17284.68	40875.99	6040.81	18690.31	17388.82	4444.81
Train 14	445035.41	146217.19	873006.51	27015.18	29017.56	12723.74	19964.82	2773.76
Test 14	28997.77	377267.67	71368.74	107157.97	5043.77	22257.87	25912.74	6375.72
Train 21	667271.19	230578.59	1075023.62	43444.73	31731.82	10768.37	26608.89	2806.22
Test 21	28105.31	1147611.83	246277.95	207970.03	4936.3	22706.61	30160.83	7056.76
Train 30	941923.57	297501.25	1375049.59	86625.4	36162.97	12782.22	34437.58	3063.81
Test 30	39144.99	2740984.16	782585.62	395002.04	6565.9	33405.66	27506.52	7493.87