# An Improved COVID-19 Forecasting by Infectious Disease Modelling Using Machine Learning
## 4 Results
### Results of the Machine Learning Models
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Countries** & **Models** & \multicolumn{3}{c}{**Recovered Cases**} \\ \hline  & & **RMSE** & **MAE** & \(\mathbf{R^{2}}\) \\ \hline \multirow{3}{*}{Saudi Arabia} & \multicolumn{1}{c}{Liener Regression} & 83,255.07 & 82,986.14 & -11,066.8 \\  & PR & 8083.33 & 6329.03 & -103.33 \\  & SVR & 218,510.45 & 216,320.95 & -76,239.4 \\ \hline \multirow{3}{*}{Bahrain} & \multicolumn{1}{c}{Liener Regression} & -130.4 & 97,633.80 & 97,618.07 \\  & PR & \(-1551.54\) & 20,214.07 & 17,260.02 \\  & SVR & \(-8874.03\) & 59,873.90 & 59,318.44 \\ \hline \multirow{3}{*}{Kuwait} & \multicolumn{1}{c}{Liener Regression} & 152,385.09 & 152,360.41 & \(-132,6795452.6\) \\  & PR & 4302.93 & 3504.65 & \(-8.71\) \\  & SVR & 90,132.26 & 89,181.64 & \(-4260.35\) \\ \hline \multirow{3}{*}{UAE} & \multicolumn{1}{c}{Liener Regression} & 34,702.00 & 34,291.25 & \(-24.12\) \\  & PR & 777/0.93 & 6535.61 & \(-0.25\) \\ \cline{1-1}  & SVR & 23,674.16 & 23,442.58 & \(-10.69\) \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Comparison of machine learning models (linear regression, PL, SVR) in terms of different error measures. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Countries** & **Models** & \multicolumn{3}{c}{**Death Cases**} \\ \hline  & & **RMSE** & **MAE** & \(\mathbf{R^{2}}\) \\ \hline \multirow{3}{*}{Kuwait} & \multicolumn{1}{c}{Liener Regression} & 62.36 & 60.98 & \(-221.2\) \\  & PR & 71.18 & 59.38 & \(-288.5\) \\  & SVR & 495.07 & 489.64 & \(-14,003.1\) \\ \hline \multirow{3}{*}{UAE} & \multicolumn{1}{c}{Liener Regression} & 49.42 & 47.21 & \(-2.83\) \\  & PR & 18.25 & 13.19 & 0.47 \\ \cline{1-1}  & SVR & 144.48 & 143.46 & \(-31.76\) \\ \hline \hline \end{tabular}
\end{table} 
Table 5: \(Cont.\)  
Figure 6: The ML forecasting for KSA Confirmed cases (Saudi Arabia). Figure 8 shows the fit of the ML models for Kuwait infected cases; the polynomial regression model is considered the optimal ML model in fitting the actual data. Figure 8: The ML forecasting for confirmed cases (KUWAIT). Figure 7: The ML forecasting for confirmed cases (BAHRAIN). Figure 9 shows the fit of the ML models for UAE infected cases; the polynomial regression model is considered the optimal ML model in fitting the actual data. Figure 10 shows the fit of the ML models for Saudi Arabian recovered cases; the polynomial regression model is considered the optimal ML model in fitting the actual data. Figure 10: The ML forecasting for recovered cases (Saudi Arabia). Figure 9: The ML forecasting for confirmed cases (UAE). Figure 11 shows the fit of the ML models for Bahrain recovered cases; the polynomial regression model is considered the optimal ML model in fitting the actual data. Figure 12 shows the fit of the ML models for Kuwait recovered cases; the polynomial regression model is considered the optimal ML model in fitting the actual data. Figure 11: The ML forecasting for recovered cases (Bahrain). Figure 12: The ML forecasting for recovered cases (Kuwait). Figure 13 shows the fit of the ML models for UAE recovered cases; the polynomial regression model is considered the optimal ML model in fitting the actual data. Figure 14 shows the fit of the ML models for Saudi Arabian death cases; the polynomial regression model is considered the optimal ML model in fitting the actual data. Figure 14: The ML forecasting for death cases (Saudi Arabia). Figure 13: The ML forecasting for recovered cases (UAE). Figure 15 shows the fit of the ML models for Bahrain death cases; the linear regression model is considered the optimal ML model in fitting the actual data. Figure 16 shows the fit of the ML models for Kuwait death cases; the polynomial regression model is considered the optimal ML model in fitting the actual data. Figure 6:0 The ML forecasting for death cases (Kuwait). Figure 6:1 The ML forecasting for death cases (Bahrain). Figure 17 shows the fit of the ML models for UAE death cases; the polynomial regression model is considered the optimal ML model in fitting the actual data.