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

Table 3

RAE values of logistic regression models for confirmed cases.

Forecast period (days)	Cumulative cases				Daily cases
	Germany	Japan	South Korea	Ukraine	Germany	Japan	South Korea	Ukraine
Train 3	0.099456	0.096796	0.016089	0.097866	0.863515	0.728601	1.374757	1.029529
Test 3	13.738489	12.770641	2.036247	2.242518	1.178802	2.506698	0.431483	3.609915
Train 7	0.134811	0.150769	0.03169	0.241352	0.872565	0.799443	1.169796	0.98824
Test 7	9.055444	7.346437	1.996374	1.767298	1.159893	1.000194	1.29776	2.164758
Train 14	0.167535	0.186455	0.081135	0.425016	0.908747	0.854744	1.185605	1.133903
Test 14	7.280291	4.480851	3.934655	2.515279	1.140845	1.144672	1.592753	2.101503
Train 21	0.228582	0.205483	0.118545	0.514556	0.953292	0.894041	1.321449	1.235317
Test 21	5.813652	3.54859	3.493077	2.35823	1.10771	1.08358	1.494972	1.998267
Train 30	0.226416	0.232743	0.16839	0.624543	0.95244	0.708316	1.323798	1.315643
Test 30	5.064591	3.096156	3.140794	2.235595	1.251722	1.077815	1.263328	1.588201