## 5 Experimental Results
### Evaluation Results
MBHO--correlation achieved an accuracy of 0.86 and an F1 score of 0.83 in 19:16:256 with 1064 features, while BCS--correlation achieved an accuracy of 0.81 and an F1 score of 0.77 in 9:56:465 with 1069 features. For the \"Leukemia\" dataset, both MBHO--correlation and BCS--correlation achieved an accuracy of 0.99 and an F1 score of 0.94, but MBHO--correlation took more time (54:23:664) and used more features (1732) than BCS--correlation (31:49:948 time and 1730 features). When using an LR classifier, here are sample instances from the results for the \"SR-BCT\" dataset. MBHO--correlation achieved an accuracy of 0.98 and an F1 score of 0.94 in 30:13:617 when selecting 1201 features while BCS--correlation achieved the same accuracy with an F1 score of 0.93 in 15:04:977 while selecting 1141 features. In the \"Leukemia\" dataset, both MBHO and BCS--correlation achieved an accuracy of 0.95 and an F1 score of 0.92, but MBHO--correlation took more time (54:23:664) and used more features (1732) than BCS--correlation (31:49:948 time and 1730 features). Under the XGBoost classifier with ten trees, here are sample instances from the results for the \"SR-BCT\" dataset. MBHO--correlation achieved an accuracy of 0.97 and an F1 score of 0.90 in 30:13:617 while using 1201 features, while BCS achieved the same accuracy and F1 score in 15:04:977 with 1141 features. In the \"Darwin\" dataset, MBHO--correlation achieved an accuracy of 0.87, an F1 score of 0.87, and an AUC of 0.97, while BCS--correlation achieved an accuracy of 0.97, and an AUC of 0.97, while BCS--correlation achieved an accuracy of 0.97, and an AUC of 0.97, respectively. \begin{table}
\begin{tabular}{r r r r r r r r r r r r r r} \hline \hline \multicolumn{1}{c}{**Name**} & \multicolumn{4}{c}{**MBHO—No Correlation**} & \multicolumn{4}{c}{**BCS—No Correlation**} \\ \hline  & **Acc** & **F1** & **Precision** & **Recall** & **AUC** & **Time** & **Features** & **Acc** & **F1** & **Precision** & **Recall** & **AUC** & **Time** & **Features** \\ \hline Colon & **0.82** & 0.82 & 0.82 & 0.82 & Nan & 621:686 & 997 & 0.79 & 0.79 & 0.79 & Nan & 10:32:061 & 972 \\ Darwin & **0.86** & 0.86 & 0.86 & 0.86 & Nan & 30:4625 & 260 & 0.80 & 0.79 & 0.80 & 0.80 & Nan & 159:366 & 257 \\ Leukemia & **0.99** & 0.94 & 0.99 & 0.99 & Nan & 9:19:25 & 1702 & **0.89** & 0.94 & 0.99 & 0.99 & [PERSON] & 629:548 & 1706 \\ Leukemia-3c & 0.97 & 0.87 & 0.97 & 0.77 & [PERSON] & 25:21:440 & 3619 & 0.96 & 0.87 & 0.96 & 0.96 & [PERSON] & 182:20:05 & 3517 \\ MLL & **0.93** & 0.85 & 0.93 & 0.93 & [PERSON] & 49:20:481 & 6223 & **0.93** & 0.85 & 0.93 & 0.93 & [PERSON] & 34:35:559 & 6188 \\ WDBC & **0.95** & 0.94 & 0.95 & 0.95 & [PERSON] & 48:443 & 10 & **0.95** & 0.94 & 0.95 & 0.95 & [PERSON] & 34:002 & 11 \\ SBRCT & **0.95** & 0.91 & 0.95 & 0.95 & [PERSON] & 7:58:261 & 1250 & 0.93 & 0.86 & 0.86 & 0.86 & [PERSON] & 42:47:249 & 1127 \\ Scholar & **0.94** & 0.85 & 0.94 & 0.94 & [PERSON] & 31:860 & 8 & **0.94** & 0.85 & 0.94 & 0.94 & [PERSON] & 19:685 & 14 \\ Parkinson’s & 0.81 & 0.87 & 0.91 & 0.91 & [PERSON] & 45:745 & 7.0 & 0.85 & 0.90 & 0.90 & [PERSON] & 29:326 & 4 \\ Sonar & **0.90** & 0.90 & 0.90 & 0.90 & [PERSON] & 47:031 & 26 & 0.88 & 0.87 & 0.88 & 0.88 & [PERSON] & 32:396 & 36 \\ Duvore & **0.98** & 0.98 & 0.98 & 0.98 & [PERSON] & 52:827 & 8 & **0.98** & 0.97 & 0.98 & 0.98 & [PERSON] & 21:664 & 18 \\ SpectTF & **0.82** & 0.74 & 0.82 & 0.82 & Nan & 48:876 & 25 & **0.82** & 0.71 & 0.82 & 0.82 & Nan & 36733 & 22 \\ Urban & **0.75** & 0.68 & 0.75 & 0.75 & Nan & 26:0484 & 89 & 0.71 & 0.65 & 0.71 & 0.71 & Nan & 56:283 & 102 \\ WPBC & **0.77** & 0.65 & 0.77 & 0.77 & Nan & 37:776 & 13 & 0.75 & 0.65 & 0.75 & 0.75 & Nan & 27:797 & 15 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Comparison between MBHO with no correlation and Binary CS [37] with no correlation based on KNN classifier with \(k=3\) and \(SL=0.05\). MBHO—no correlation outperformed; BCS—no correlation [37] in eight datasets for the _Acc_. It achieved the same results with the remaining datasets for _Acc_.