## 5 Experiment and Results
### Metaheuristic Algorithms Comparison  
A comparison between the accuracy and F-measure values for the proposed WOA-SVM and the other meta-heuristic algorithms is discussed in this section.  
Tables 8 and 9 show the accuracy values for the first-rules and latter-rules datasets, respectively. It is observed from Table 4 that the proposed approach outperforms the other approaches for Data 2, Data 4, and Data 5. However, the PSO-SVM outperforms the proposed approach for Data 1 and Data 3, but the proposed approach still outperforms the GA-SVM and MVO-SVM for these datasets. As for the latter-rules datasets, the proposed WOA-SVM approach outperforms the other algorithms for all the datasets except the Data 9 dataset.  
Looking at the other tables considering the F-measure, which are Tables 10 and 11, similar observations can be observed. WOA-SVM outperforms the other algorithms for Data 2 and Data 4 but PSO-SVM has higher F-measure values for Data 1, Data 3, and Data 5. On the other hand, and for the latter-rules datasets in Table 11, the proposed approach outperforms the other algorithms for all the datasets except the Data 9 dataset, which is also observed from the accuracy values in Table 9.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Datasets**} & \multicolumn{2}{c}{**GA-SVM**} & \multicolumn{2}{c}{**PSO-SVM**} & \multicolumn{2}{c}{**MVO-SVM**} & \multicolumn{2}{c}{**WOA-SVM**} \\ \cline{2-9}  & **Avg** & **Std** & **Avg** & **Std** & **Avg** & **Std** & **Avg** & **Std** \\ \hline Data 1 & 78.56\% & 4.19\% & **80.82\%** & 2.45\% & 78.83\% & 3.51\% & 79.03\% & 3.40\% \\ Data 2 & 78.03\% & 3.62\% & 79.28\% & 1.84\% & 80.12\% & 2.64\% & **80.36\%** & 3.06\% \\ Data 3 & 78.62\% & 3.97\% & **81.60\%** & 2.63\% & 77.92\% & 2.75\% & 81.12\% & 3.35\% \\ Data 4 & 78.73\% & 3.83\% & 80.50\% & 3.12\% & 78.02\% & 4.44\% & **81.96\%** & 1.73\% \\ Data 5 & 77.36\% & 2.48\% & **80.66\%** & 2.44\% & 79.76\% & 2.93\% & 80.66\% & 2.04\% \\ \hline \hline \end{tabular}
\end{table}
Table 10: F-measure results of GA-SVM, PSO-SVM, WOA-SVM, and MVO-SVM for First-rules datasets.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Datasets**} & \multicolumn{2}{c}{**GA-SVM**} & \multicolumn{2}{c}{**PSO-SVM**} & \multicolumn{2}{c}{**MVO-SVM**} & \multicolumn{2}{c}{**WOA-SVM**} \\ \cline{2-9}  & **Avg** & **Std** & **Avg** & **Std** & **Avg** & **Std** \\ \hline Data 1 & 67.88\% & 6.72\% & **71.64\%** & 3.88\% & 68.87\% & 5.28\% & 69.05\% & 4.61\% \\ Data 2 & 68.47\% & 3.80\% & 70.15\% & 2.70\% & 71.19\% & 4.35\% & **72.05\%** & 2.96\% \\ Data 3 & 67.60\% & 6.04\% & **73.73\%** & 2.80\% & 66.29\% & 3.80 & 72.73\% & 4.71\% \\ Data 4 & 68.50\% & 5.54\% & 71.87\% & 4.75\% & 67.52\% & 7.11\% & **73.64\%** & 2.58\% \\ Data 5 & 65.57\% & 3.09\% & 71.87\% & 3.19\% & 70.28\% & 4.94\% & **72.00\%** & 2.90\% \\ \hline \hline \end{tabular}
\end{table}
Table 8: Accuracy results of GA-SVM, PSO-SVM, MVO-SVM, and WOA-SVM for First-rules datasets.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Datasets**} & \multicolumn{2}{c}{**GA-SVM**} & \multicolumn{2}{c}{**PSO-SVM**} & \multicolumn{2}{c}{**MVO-SVM**} & \multicolumn{2}{c}{**WOA-SVM**} \\ \cline{2-9}  & **Avg** & **Std** & **Avg** & **Std** & **Avg** & **Std** & **Avg** & **Std** \\ \hline Data 1 & 67.88\% & 6.72\% & **71.64\%** & 3.88\% & 68.87\% & 5.28\% & 69.05\% & 4.61\% \\ Data 2 & 68.47\% & 3.80\% & 70.15\% & 2.70\% & 71.19\% & 4.35\% & **72.05\%** & 2.96\% \\ Data 3 & 67.60\% & 6.04\% & **73.73\%** & 2.80\% & 66.29\% & 3.80 & 72.73\% & 4.71\% \\ Data 4 & 68.50\% & 5.54\% & 71.87\% & 4.75\% & 67.52\% & 7.11\% & **73.64\%** & 2.58\% \\ Data 5 & 65.57\% & 3.09\% & 71.87\% & 3.19\% & 70.28\% & 4.94\% & **72.00\%** & 2.90\% \\ \hline \hline \end{tabular}
\end{table}
Table 8: Accuracy results of GA-SVM, PSO-SVM, MVO-SVM, and WOA-SVM for First-rules datasets.