# Binary Starling Murmutation Optimizer Algorithm to Select Effective Features from Medical Data
## Appendix A
\begin{table}
\begin{tabular}{l l c c c c c c c c c} \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 S1-BSMO & Avg & 88.7609 & 93.8971 & 68.6377 & 99.2675 & 88.365 & 93.4924 & 68.8162 & 99.2336 \\  & Max & 90.2278 & 96.2467 & 85.3876 & 99.7684 & 89.7842 & 95.292 & 78.4811 & 100 \\ \hline S2-BSMO & Avg & 88.3668 & 93.6035 & 71.8856 & 99.3568 & 88.22 & 92.9212 & 69.6659 & 99.3498 \\  & Max & 89.1665 & 95.3642 & 84.1441 & 99.8295 & 89.7151 & 95.2571 & 79.7631 & 100 \\ \hline S3-BSMO & Avg & 88.1191 & 93.0296 & 72.7952 & 99.3912 & 88.0791 & 93.0515 & 69.5805 & 99.383 \\  & Max & 89.0592 & 95.2235 & 85.8833 & 100 & 89.7059 & 95.8368 & 79.1405 & 100 \\ \hline S4-BSMO & Avg & 88.191 & 93.1775 & 72.6372 & 99.4499 & 88.0248 & 93.0834 & 71.6037 & 99.2982 \\  & Max & 89.0733 & 95.3049 & 81.5983 & 100 & 89.4038 & 96.6535 & 88.5142 & 99.7212 \\ \hline V1-BSMO & Avg & 88.3628 & 94.2365 & 78.835 & 99.9088 & 88.327 & 94.012 & 76.679 & 99.504 \\  & Max & 89.4449 & 95.5444 & 88.3507 & 100 & 89.715 & 94.952 & 85.144 & 100 \\ \hline V2-BSMO & Avg & 87.6423 & 94.536 & 79.637 & 99.9252 & 87.515 & 93.419 & 80.879 & 99.696 \\  & Max & 88.1193 & 96.3431 & 90.6895 & 100 & 88.523 & 94.47 & 88.078 & 100 \\ \hline V3-BSMO & Avg & 87.8565 & 94.0807 & 79.3312 & 99.8619 & 88.05 & 94.206 & 75.106 & 99.811 \\  & Max & 88.9304 & 96.2699 & 86.7033 & 100 & 89.359 & 95.947 & 83.572 & 100 \\ \hline V4-BSMO & Avg & 88.4581 & 94.1059 & 80.3357 & 99.8371 & 88.104 & 93.948 & 78.811 & 99.775 \\  & Max & 89.115 & 95.4339 & 89.9166 & 100 & 89.716 & 94.769 & 91.569 & 100 \\ \hline Threshold- & Avg & 89.0468 & 94.655 & 80.116 & 99.3936 & 88.503 & 94.575 & 75.676 & 99.348 \\ BSMO & Max & 91.0607 & 96.4165 & 88.838 & 100 & 89.44 & 96.612 & 84.286 & 99.548 \\ \hline \multicolumn{10}{c}{\(k\) = 5, \(N\) = 30} & \multicolumn{6}{c}{\(k\) = 7, \(N\) = 30} \\ \cline{3-10}  & \multicolumn{2}{c}{Diabetes} & Heart & \multicolumn{1}{c}{Hepatics} & \multicolumn{1}{c}{COVID-19} & \multicolumn{1}{c}{Diabetes} & Heart & \multicolumn{1}{c}{Hepatics} & \multicolumn{1}{c}{COVID-19} \\ \hline S1-BSMO & Avg & 88.5142 & 93.6608 & 70.6404 & 99.2906 & 88.514 & 93.831 & 71.703 & 99.26 \\  & Max & 89.8454 & 95.0876 & 80.2298 & 99.7496 & 89.311 & 95.569 & 88.021 & 99.609 \\ \hline S2-BSMO & Avg & 88.2422 & 93.3517 & 70.8924 & 99.3947 & 88.387 & 93.475 & 67.965 & 99.381 \\  & Max & 89.2631 & 95.3351 & 84.532 & 100 & 89.719 & 94.748 & 75.613 & 99.822 \\ \hline S3-BSMO & Avg & 88.1787 & 93.1475 & 71.8705 & 99.3703 & 88.325 & 92.863 & 69.775 & 99.512 \\  & Max & 90.1796 & 94.4033 & 85.8738 & 100 & 90.142 & 95.51 & 75.39 & 100 \\ \hline S4-BSMO & Avg & 88.3085 & 93.2132 & 72.851 & 99.4093 & 88.234 & 93.467 & 74.89 & 99.486 \\  & Max & 89.7088 & 95.0297 & 82.1369 & 100 & 88.447 & 96.508 & 90.417 & 100 \\ \hline V1-BSMO & Avg & 88.2848 & 93.8571 & 78.8832 & 99.8598 & 88.244 & 94.334 & 78.981 & 99.861 \\  & Max & 89.7132 & 96.2621 & 85.8624 & 100 & 88.978 & 96.082 & 87.181 & 100 \\ \hline V2-BSMO & Avg & 88.6261 & 94.4918 & 79.3521 & 99.8182 & 88.217 & 94.237 & 76.884 & 99.87 \\  & Max & 90.0085 & 96.2525 & 87.3972 & 100 & 89.536 & 96.225 & 85.649 & 100 \\ \hline V3-BSMO & Avg & 88.245 & 94.1042 & 78.5909 & 99.7693 & 88.328 & 94.287 & 78.435 & 99.707 \\  & Max & 89.6911 & 95.6443 & 86.1964 & 100 & 89.598 & 96.606 & 85.285 & 100 \\ \hline V4-BSMO & Avg & 88.1009 & 94.0096 & 79.7051 & 99.7845 & 88.377 & 94.327 & 77.526 & 99.802 \\  & Max & 89.484 & 95.4345 & 88.4275 & 100 & 89.576 & 95.545 & 84.209 & 100 \\ \hline Threshold- & Avg & 89 & 94.6804 & 80.2438 & 99.3774 & 89.1512 & 94.8397 & 81.5161 & 99.4531 \\ BSMO & Max & 89.9871 & 96.6626 & 91.3715 & 100 & 90.8328 & 96.8864 & 81.5161 & 100 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Parameters setting of BSMO algorithm in terms of sensitivity values.