## 5 Experimental Evaluation
### COVID-19 Vaccination Forecast for the USA
#### 5.3.2 Partially Vaccinated Population Prediction  
The predicted outputs for partially vaccinated population of the USA for a period of 60 days (2 months) from our model classifier is shown in Figure 15. We also performed a prediction for the timeline 4 July 2021 to see the estimated percentage if it aligns with the US government expectations. The prediction accuracy and error for different models are given in Table 8. As for KNN and RF, the classifier does not work well, thus we do not mention the numbers in the table to keep it simple. For the 4 July forecast, SVM, M5 model tree, and MLP all have 100% DAC. SVM has the lowest MAPE and RAE among these three models. Using SVM, the model predicts that around 57.62% of the US population will get at least one dose of vaccine. If we consider only the adult population [67], this percentage becomes 73.53%, which is nearly the expected percentage (70%) given by US President [PERSON] [68].  
For the 2-month prediction period, all models have 100% DAC. Of all other methods, MLP has the lowest error and is considered as the best classifier for the 2-month forecasting. Thus, using MLP, we can predict that by 25 July 2021 around 80% of the US adult population will get at least one dose of vaccine against COVID-19.  
\begin{table}
\begin{tabular}{l c c c c c c c c c c c c} \hline \hline
**Forecast Time-Unit** & \multicolumn{5}{c}{**39 Days [4 July 2021]**} & \multicolumn{5}{c}{**2 Month [25 July 2021]**} \\ \hline
**ML Model** & **RRSE** & **RAE** & **MAPE** & **DAC** & **RRSE** & **RAE** & **MAPE** & **DAC** & **Predicted Output [25 July (5)]** & **Population** \\
**MLE Model** & **RRSE** & **RAE** & **MAPE** & **DAC** & **RPSE** & **RAE** & **MAPE** & **DAC** & **Predicted Population (5x)** & **Population** (5x)** \\ \hline
**SVM** & 9.6839 & 7.9317 & 1.0053 & 100 & **0.7** & **0.611** & **0.4085** & **100** & 158.87538530 & **47.998** \\ KNN & 33.2298 & 16.3643 & 1.5781 & 97.2603 & 5.4676 & 3.5357 & 2.2319 & 95.2381 & 127.340119.67 & 38.471 \\ LR & 22.2554 & 19.3558 & 2.1925 & 98.6301 & 19.7441 & 9.0889 & 6.2373 & 70 & 244.33203.02 & 73.817 \\ RF & 5.1035 & 3.8572 & 0.3873 & 97.2603 & 0.518 & 0.4019 & 0.2706 & 100 & 130.38669.58 & 39.452 \\ MS & 12.5465 & 10.6901 & 1.1793 & 100 & 1.1796 & 0.9642 & 0.6379 & 100 & 206.719983.86 & 62.453 \\ Gaussian & 97.8654 & 89.2647 & 10.6584 & 83.7838 & 6.6613 & 5.7836 & 3.8304 & 100 & 389.53037.65 & 117.682 \\ MLP & 8.3574 & 7.1726 & **0.7369** & **100** & 0.8495 & 0.7206 & 0.4823 & 100 & 165,131,860.07 & 49.888 \\ \hline \hline \end{tabular}
\end{table}
Table 7: Prediction accuracy and error for different machine learning models to forecast fully vaccinated population in the USA.  
\begin{table}
\begin{tabular}{l c c c c c c c c c c c c} \hline \hline
**Forecast Time-Unit** & \multicolumn{5}{c}{**39 Days [4 July 2021]**} & \multicolumn{5}{c}{**2 Month [25 July 2021]**} \\ \hline
**ML Model** & **RRSE** & **RAE** & **MAPE** & **DAC** & **Predicted Population** & **Population** & **RPSE** & **RAE** & **MAPE** & **DAC** & **Predicted Population (5x)** & **Population** (5x)** \\
**SVM** & **1.15** & **1.03** & **0.38** & **100** & 190723,081.48 & **57.62** & 0.77 & 0.63 & 0.33 & 100 & 202.710/056.47 & 61.24 \\ LR & 2.51 & 1.94 & 0.74 & 98.63 & 183,414,075.51 & 55.41 & 0.76 & 0.69 & 0.36 & 100 & 190.327481.30 & 57.50 \\ MS & 3.66 & 3.41 & 1.24 & 100 & 206,800,303.67 & 62.48 & 2.29 & 1.96 & 1.00 & 100 & 227.4257103