# Ensemble Machine Learning for Monkeypox Transmission Time Series Forecasting
## 3 Results and Discussion  
The section presents the results and discusses the major findings from our experiments. Experiments were performed using the Jupiter notebook (Python 3.9 version) programming environment. The Python programming language was used for training and testing all the models used in this work. The Python libraries used in this paper are Numpy, Matplotlib, Sklearn, Pandas, Math, Seaborn, Scipy, and Time. The COVID-19 dataset was used for training the machine learning models, while the monkey pox dataset was used for testing the models. Experimental results of the original COVID-19 dataset that was used for training our model is already reported in our previous work [99]. The reason for using the COVID-19 dataset for training is that it is also an epidemic, just like monkey pox. COVID-19 has a large dataset, which the machine learning algorithms can easily learn from. However, the dataset for monkey pox is not so big, and is therefore more suitable for testing the trained models. The virus that causes monkey pox is a newly discovered infectious illness that affects people and is typically spread by rodents. \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**All Models Were Trained Using Scikit Learn** & **Hyperparameter** & **Values** \\ \hline \multirow{4}{*}{Adaboost} & n\_estimators & 50 \\ \cline{2-3}  & learning\_rate & 0.2 \\ \cline{2-3}  & Loss & Exponential \\ \hline \multirow{3}{*}{RFR} & n\_estimators & 400 \\ \cline{2-3}  & Random\_state & 0 \\ \hline OLS & Alpha & 0.1 \\ \hline LASSO & Alpha & 0.1 \\ \hline \multirow{6}{*}{GBOOST} & n\_estimators & 400 \\ \cline{2-3}  & max\_depth & 5 \\ \cline{2-3}  & Loss & Squared\_error \\ \cline{2-3}  & min\_samples\_split & 2 \\ \cline{2-3}  & learning\_rate = 0.1 & 0.1 \\ \hline RIDGE & Alpha & 0.1 \\ \hline SEL & n\_estimators & 400 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Experimental configuration and parameters tuning of Adaboost, GBOOST, RF, OLS, LASSO, RIDGE and SEL. Although it can spread to other individuals, an epidemic cannot be readily sustained by person-to-person transmission alone. The clinical appearance is less severe but similar to that of smallpox in the past. Although smallpox was eliminated from the world in 1980, monkey pox still periodically arises in areas of Central and West Africa that are close to tropical rainforests. Monkey pox epidemics have historically had a 1-10% case fatality rate, but with the right care, many patients will recover. Health professionals in charge of monkey pox prevention and control are the target audience for this research, which gives a general introduction to the disease. This paper considered the different continents that have experienced outbreaks of monkey pox. Figure 2 displays hospitalized cases of monkey pox in Africa, Asia, Europe, North America, South America, and Oceania. Africa and North America had the lowest number of people that were hospitalized (0.0%), while Oceania came in second with 2.6%. The European continent has the highest number of people hospitalized with cases of monkey pox, at 89.7%. Figure 3 shows the confirmed cases of monkey pox, with North America having the lowest with 0.2%, followed by Oceania with 0.3%, while the European continent has the highest number of confirmed cases with 97.6%. Figure 4 shows the suspected cases of monkey pox, with Africa, Asia, North America, and Oceania having the lowest with 1.6%. The European continent has the highest, with 75.8%. Figure 5 is the pie chart of the suspected travel history of monkey pox patients. Europe has the highest rate with 72.2%, followed by South America with 12.7%. The African continent had the lowest percentage, at 0.8%. Figure 6 is the pie chart of suspected cases of monkey pox with no travel history. The result showed that Europe is leading with 87.9%, while Asia, Oceania, and North America are the lowest with 1.5%. Figure 7 is the time series of monkey pox from 6 May 2022 to 24 June 2022.