Research Article
Effective Utilization of Data for Predicting COVID-19 Dynamics: An Exploration through Machine Learning Models
Table 2
MAE values of logistic regression models for fatal cases.
| Forecast period (days) | Cumulative cases | Daily cases | Germany | Japan | South Korea | Ukraine | Germany | Japan | South Korea | Ukraine |
| Train 3 | 10594.46 | 4389.47 | 779.36 | 2137.49 | 93.7 | 37.72 | 43.5 | 186.8 | Test 3 | 875 | 7401 | 60.33 | 221.33 | 68 | 59.33 | 7 | 22.67 | Train 7 | 14431.7 | 5036.62 | 1455.71 | 4339.38 | 96.37 | 41.63 | 41.45 | 186.37 | Test 7 | 1046.57 | 5552.86 | 129.57 | 511.43 | 53.29 | 67.86 | 14.43 | 27.29 | Train 14 | 17803.87 | 6076.29 | 2126.05 | 6719.15 | 102.1 | 46 | 41.38 | 187.03 | Test 14 | 1252.86 | 5299.07 | 275.21 | 1036.36 | 55.43 | 78.07 | 19.43 | 31.79 | Train 21 | 18747.84 | 6258.6 | 2283.06 | 8983.12 | 109.16 | 49.14 | 43.62 | 183.2 | Test 21 | 1413.81 | 6149.38 | 453.9 | 1665.52 | 45.05 | 76.19 | 21.86 | 44.38 | Train 30 | 20143.5 | 6774.49 | 2284.55 | 11098.24 | 115.11 | 48.62 | 45.96 | 185.85 | Test 30 | 1567.74 | 7479.45 | 762.58 | 2716.65 | 45.1 | 83.74 | 24.1 | 57.29 |
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