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

Table 19

Accuracy of models (%).

Data	Germany	Japan	South Korea	Ukraine
Logistic regression
Cumulative new cases	99.95162	99.70030	99.86759	99.87374
Daily new cases	99.41299	96.77574	99.72373	99.61698
Cumulative fatal cases	99.98934	99.79289	99.97083	99.97365
Daily fatal cases	98.11139	98.16951	99.54319	99.70875
Decision tree
Cumulative new cases	99.97758	99.80331	99.91879	99.89274
Daily new cases	98.85702	96.77574	99.63523	99.73622
Cumulative fatal cases	99.99430	99.91407	99.97161	99.97365
Daily fatal cases	99.41889	97.39953	99.67860	99.77845
Support vector regression
Cumulative new cases	99.99877	99.84280	99.96544	99.91326
Daily new cases	99.65751	99.71199	99.73819	99.73169
Cumulative fatal cases	99.99663	99.92004	99.99924	99.99049
Daily fatal cases	95.65136	99.71555	99.76044	99.73247