# Binary Starling Murmutation Optimizer Algorithm to Select Effective Features from Medical Data
## Appendix A
\begin{table}
\begin{tabular}{l l l l l l l l l l l} \hline \hline \multirow{2}{*}{**Algorithms**} & \multirow{2}{*}{**Metrics**} & \multicolumn{6}{c}{\(k\) = 3, \(N\) = 30} & \multicolumn{6}{c}{\(k\) = 5, \(N\) = 20} \\ \cline{3-10}  & & **Diabetes** & **Heart** & **Hepatics** & **COVID-19** & **Diabetes** & **Heart** & **Hepatics** & **COVID-19** \\ \hline \multirow{2}{*}{S1-BSMO} & Avg & 76.9228 & 85.7901 & 88.1236 & 95.4467 & 76.8885 & 85.5802 & 88.1083 & 95.401 \\  & Max & 77.3257 & 86.6667 & 89.125 & 95.5961 & 77.4761 & 86.2963 & 90.2917 & 95.707 \\ \hline \multirow{2}{*}{S2-BSMO} & Avg & 76.8251 & 85.4568 & 88.1625 & 95.364 & 76.717 & 85.4444 & 88.0736 & 95.3321 \\  & Max & 77.3582 & 86.2963 & 89.75 & 95.5921 & 77.4761 & 86.2963 & 89.625 & 95.4852 \\ \hline \multirow{2}{*}{S3-BSMO} & Avg & 76.6528 & 85.4198 & 88.3667 & 95.3389 & 76.677 & 85.2222 & 87.9167 & 95.2899 \\  & Max & 77.0899 & 86.2963 & 89.6667 & 95.4852 & 77.9973 & 86.2963 & 89.0417 & 95.4878 \\ \hline \multirow{2}{*}{S4-BSMO} & Avg & 76.7293 & 85.3086 & 88.0444 & 95.3477 & 76.6684 & 85.0988 & 87.9708 & 95.3 \\  & Max & 77.2198 & 85.9259 & 89.125 & 95.4878 & 77.0933 & 86.2963 & 89.875 & 95.4838 \\ \hline \multirow{2}{*}{V1-BSMO} & Avg & 76.9143 & 86 & 89.2708 & 95.2115 & 76.707 & 86 & 89.158 & 95.197 \\  & Max & 77.218 & 86.6667 & 90.375 & 95.4758 & 77.088 & 86.296 & 90.333 & 95.362 \\ \hline \multirow{2}{*}{V2-BSMO} & Avg & 76.9203 & 86.0617 & 89.2958 & 95.2158 & 76.644 & 85.926 & 89.229 & 95.238 \\  & Max & 77.0779 & 86.2963 & 90.375 & 95.3635 & 76.822 & 86.296 & 89.833 & 95.364 \\ \hline \multirow{2}{*}{V3-BSMO} & Avg & 76.9173 & 86.0741 & 89.3458 & 95.2694 & 76.834 & 85.951 & 89.211 & 95.268 \\  & Max & 77.2095 & 86.6667 & 90.4583 & 95.3729 & 77.227 & 86.296 & 90.292 & 95.595 \\ \hline \multirow{2}{*}{V4-BSMO} & Avg & 76.9872 & 86.0864 & 89.3708 & 95.2895 & 76.876 & 85.951 & 89.289 & 95.204 \\  & Max & 78.0041 & 86.2963 & 90.375 & 95.83 & 77.081 & 86.296 & 90.333 & 95.481 \\ \hline \multirow{2}{*}{Threshold-BSMO} & Avg & 77.3771 & 86.5309 & 89.8972 & 95.5124 & 77.136 & 86.37 & 88.919 & 95.467 \\  & Max & 78.1203 & 87.4074 & 91.5 & 95.715 & 77.862 & 87.037 & 90.542 & 95.599 \\ \hline \multirow{2}{*}{Algorithms} & \multicolumn{6}{c}{\(k\) = 5, \(N\) = 30} & \multicolumn{6}{c}{\(k\) = 7, \(N\) = 30} \\ \cline{3-10}  & \multicolumn{2}{c}{Diabetes} & Heart & \multicolumn{1}{l}{Hepatics} & \multicolumn{1}{l}{COVID-19} & \multicolumn{1}{l}{Diabetes} & Heart & \multicolumn{1}{l}{Hepatics} & \multicolumn{1}{l}{COVID-19} \\ \hline \multirow{2}{*}{S1-BSMO} & Avg & 76.9719 & 85.8148 & 87.8319 & 95.417 & 76.895 & 85.778 & 88.189 & 95.427 \\  & Max & 77.7409 & 86.2963 & 89 & 95.5988 & 77.216 & 86.667 & 88.958 & 95.599 \\ \hline \multirow{2}{*}{S2-BSMO} & Avg & 76.8537 & 85.5185 & 88.1708 & 95.3861 & 76.927 & 85.704 & 88.3 & 95.389 \\  & Max & 77.7341 & 85.9259 & 89.1667 & 95.5961 & 77.344 & 86.296 & 89.542 & 95.482 \\ \hline \multirow{2}{*}{S3-BSMO} & Avg & 76.6101 & 85.3333 & 88.2153 & 95.3308 & 76.763 & 85.457 & 88.192 & 95.336 \\  & Max & 77.4897 & 85.9259 & 89.9167 & 95.6001 & 76.965 & 85.926 & 89.083 & 95.482 \\ \hline \multirow{2}{*}{S4-BSMO} & Avg & 76.6654 & 85.3704 & 88.2306 & 95.3347 & 76.643 & 85.333 & 87.922 & 95.341 \\  & Max & 77.4863 & 86.2963 & 89.6667 & 95.5948 & 76.96 & 85.926 & 89.167 & 95.484 \\ \hline \multirow{2}{*}{V1-BSMO} & Avg & 76.889 & 85.9383 & 89.1542 & 95.2469 & 76.864 & 85.963 & 89.313 & 95.24 \\  & Max & 77.3411 & 86.2963 & 90.5 & 95.5974 & 77.348 & 86.296 & 90.375 & 95.376 \\ \hline \multirow{2}{*}{V2-BSMO} & Avg & 76.8872 & 86.037 & 89.2069 & 95.263 & 76.918 & 86.148 & 89.267 & 95.227 \\  & Max & 77.6128 & 86.2963 & 90.375 & 95.4812 & 77.353 & 86.296 & 89.792 & 95.365 \\ \hline \multirow{2}{*}{V3-BSMO} & Avg & 76.7716 & 86.0741 & 89.1986 & 95.2695 & 76.774 & 86.037 & 89.013 & 95.23 \\  & Max & 77.2163 & 86.6667 & 90.375 & 95.4838 & 77.075 & 86.296 & 89.583 & 95.607 \\ \hline \multirow{2}{*}{V4-BSMO} & Avg & 76.9639 & 86.0123 & 89.3278 & 95.2692 & 76.992 & 85.926 & 89.292 & 95.293 \\  & Max & 77.471 & 86.2963 & 90.375 & 95.4892 & 77.346 & 86.296 & 89.833 & 95.365 \\ \hline \multirow{2}{*}{Threshold-BSMO} & Avg & 77.3077 & 86.5309 & 89.5194