## 3 Results  
The results of the first testing stage showed accuracy ranging from 48.39% (2.24% standard deviation, 2.01 s) for the model using GNB with Dataset 2 to 92.75% (1.36% standard deviation, 11.48 s) for the model using XGB with Dataset 5 (Table 9, Figure 10). \begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**LR**} & \multicolumn{3}{c}{**LDA**} & \multicolumn{3}{c}{**SVM**} & \multicolumn{3}{c}{**KNN**} \\ \hline
**Dataset** & **Accuracy** & **Std** & \begin{tabular}{c} **Time** \\ **(Sec)** \\ \end{tabular} & **Accuracy** & **Std** & \begin{tabular}{c} **Time** \\ **(Sec)** \\ \end{tabular} & **Accuracy** & **Std** & \begin{tabular}{c} **Time** \\ **(Sec)** \\ \end{tabular} & **Accuracy** & **Std** & \
\begin{tabular}{c} **Time** \\ **(Sec)** \\ \end{tabular} & **Accuracy** & **Std** &
\begin{tabular}{c} **Time** \\ **(Sec)** \\ \end{tabular} \\ \hline
1 & 69.82\% & 2.15\% & 2.66 & 66.84\% & 2.02\% & 2.34 & 69.75\% & 2.23\% & 5.05 & 88.02\% & 1.97\% & 3.49 \\
2 & 68.03\% & 1.85\% & 2.7 & 64.74\% & 2.18\% & 2.2 & 70.20\% & 1.64\% & 5.32 & 87.77\% & 1.82\% & 3.66 \\
3 & 68.64\% & 1.87\% & 2.68 & 65.98\% & 2.32\% & 2.14 & 70.17\% & 1.75\% & 5.43 & 88.57\% & 1.38\% & 4.14 \\
4 & 67.67\% & 2.08\% & 2.52 & 65.99 & 1.47\% & 2.32 & 68.94\% & 0.85\% & 3.88 & 88.43\% & 1.91\% & 3.6 \\
5 & 71.00\% & 1.74\% & 2.52 & 65.42\% & 2.54\% & 2.32 & 69.31\% & 1.12\% & 5.25 & 87.96\% & 1.57\% & 3.86 \\
6 & 71.22\% & 1.60\% & 2.48 & 66.12\% & 1.60\% & 2.45 & 71.00\% & 1.06\% & 5.42 & 88.58\% & 1.08\% & 3.77 \\ \hline  & \multicolumn{3}{c}{**GNB**} & \multicolumn{3}{c}{**MLP**} & \multicolumn{3}{c}{**ELM**} & \multicolumn{3}{c}{**CART**} \\ \hline
**Dataset** & **Accuracy** & **Std** & \begin{tabular}{c} **Time** \\ **(Sec)** \\ \end{tabular} & **Accuracy** & **Std** & \
\begin{tabular}{c} **Time** \\ **(Sec)** \\ \end{tabular} & **Accuracy** & **Std** &
\begin{tabular}{c} **Time** \\ **(Sec)** \\ \end{tabular} \\ \hline
1 & 48.48\% & 2.89\% & 2.00 & 84.64\% & 1.80\% & 30.00 & 80.46\% & 1.30\% & 3.41 & 87.37\% & 2.18\% & 3.63 \\
2 & 48.39\% & 2.24\% & 2.01 & 87.61\% & 1.74\% & 30.12 & 85.52\% & 1.50\% & 0.95 & 87.66\% & 1.48\% & 3.59 \\
3 & 48.74\% & 2.45\% & 2.17 & 83.65\% & 1.86\% & 30.42 & 74.27\% & 3.45\% & 1.44 & 87.66\% & 1.62\% & 3.61 \\
4 & 62.07\% & 1.60\% & 2.01 & 86.33\% & 0.98\% & 22.59 & 74.78\% & 5.22\% & 0.44 & 88.02\% & 1.89\% & 3.41 \\
5 & 66.30\% & 3.32\% & 2.03 & 85.72\% & 2.03\% & 31.22 & 77.54\% & 1.78\% & 1.35 & 87.58\% & 2.30\% & 3.6 \\
6 & 66.19\% & 1.60\% & 2.21 & 86.81\% & 1.77\% & 32.35 & 76.13\% & 1.92\% & 1.01 & 87.86\% & 2.12\% & 3.59 \\ \hline  & \multicolumn{3}{c}{**RF**} & \multicolumn{3}{c}{**XGB**} \\ \hline
**Dataset** & **Accuracy** & **Std** & \begin{tabular}{c} **Time** \\ **(Sec)** \\ \end{tabular} & **Accuracy** & **Std** & \
\begin{tabular}{c} **Time** \\ **(Sec)** \\ \end{tabular} & **Accuracy** & **Std** &
\begin{tabular}{c} **Time** \\ **(Sec)** \\ \end{tabular} \\ \hline
1 & 91.60\% & 1.60\% & 1.03 & 91.57\% & 1.34\% & 13.19 \\
2 & 91.68\% & 1.76\% & 10.18 & 91.42\% & 1.60\% & 13.02 \\
3 & 91.64\% & 1.24\% & 10.39 & 91.97\% & 1.55\% & 13.02 \\
4 & 92.02\% & 1.54\% & 9.64 & 91.82\% & 1.99\% & 11.44 \\
5 & 92.73\% & 1.46\% & 9.26 & 92.75\% & 1.36\% & 11.48 \\
6 & 92.69\% & 1.48\% & 9.05 & 92.73\% & 1.68\% & 11.33 \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Testing results for the first testing stage (LR: Logistic Regression, LDA: Linear Discriminant Analysis, SVM: Support Vector Machine, KNN: K Nearest Neighbor, GNB: Gaussian Naïve Bayes, MLP: Multi-Layer Perceptron, ELM: Extreme Learning Machine, CART: Classification and Regression Trees, RF: Random Forest, XGB: xGBoost, std: standard deviation). deviation, 9.64 s); Model 4: RF with Dataset 6 (92.69% accuracy, 1.48% standard deviation, 9.05 s); model 5: XGB combined with Dataset 1 (91.57% accuracy, 1.34% standard deviation, 13.19 s); and Model 6: XGB combined with Dataset 5 (92.75% accuracy, 1.36% standard deviation, 11.48 s). All MLAs were used with their standard parameters (Table 10).