## 5 Simulations
### Simulation Results
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & & **Accuracy** & **Feature \#** & **Fitness Value** & **CPU Time** \\ \hline \multirow{6}{*}{Breastcancer} & BBA & **0.9786** & **6.0000** & **0.0272** & 69.5141 \\  & BBA-IF1 & **0.9786** & **6.0000** & **0.0272** & 64.4441 \\  & BBA-IF2 & **0.9786** & **6.0000** & **0.0272** & 67.0577 \\  & BBA-IF3 & **0.9786** & **6.0000** & **0.0272** & **60.1375** \\  & EBBA & **0.9786** & **6.0000** & **0.0272** & 60.9926 \\  & BBA & 0.9613 & 6.6000 & 0.0405 & 73.3552 \\  & BBA-IF1 & 0.9613 & **5.2333** & **0.0400** & 65.2602 \\ BreastEW & BBA-IF2 & **0.9614** & 5.9000 & 0.0402 & 68.0782 \\  & BBA-IF3 & **0.9611** & 5.4000 & 0.0403 & **63.0563** \\  & EBBA & **0.9614** & 5.4333 & **0.0400** & 63.4576 \\  & BBA & **0.9793** & 6.9000 & 0.0248 & 58.3419 \\  & BBA-IF1 & 0.9790 & 6.6667 & 0.0249 & 51.4119 \\ Congress & BBA-IF2 & 0.9783 & **6.2333** & 0.0253 & 54.6810 \\  & BBA-IF3 & 0.9791 & 6.6667 & 0.0249 & 50.4414 \\  & EBBA & **0.9793** & 6.4000 & **0.0245** & **49.2745** \\  & BBA & **1.0000** & **6.0000** & **0.0046** & 91.2861 \\  & BBA-IF1 & **1.0000** & **6.0000** & **0.0046** & 88.5090 \\ Exactly & BBA-IF2 & **1.0000** & **6.0000** & **0.0046** & 92.2044 \\  & BBA-IF3 & **1.0000** & **6.0000** & **0.0046** & 88.9417 \\  & EBBA & **1.0000** & **6.0000** & **0.0046** & **88.3184** \\  & BBA & 0.7854 & 2.2667 & 0.2142 & 86.8956 \\  & BBA-IF1 & 0.7859 & 2.0333 & 0.2136 & 81.4199 \\ Exactly2 & BBA-IF2 & 0.7848 & 2.5333 & 0.2150 & 87.3399 \\  & BBA-IF3 & 0.7848 & 2.4333 & 0.2149 & 84.0370 \\  & EBBA & **0.7868** & **1.9667** & **0.2126** & 81.4770 \\  & BBA & 0.8511 & 5.0333 & 0.1513 & 45.4301 \\  & BBA-IF1 & 0.8516 & 4.9000 & 0.1507 & 39.6087 \\ HeartEW & BBA-IF2 & **0.8521** & 5.1000 & **0.1503** & 04.7423 \\  & BBA-IF3 & 0.8511 & **4.8333** & 0.1511 & **38.9901** \\  & EBBA & 0.8520 & 5.0667 & 0.1504 & 39.0150 \\  & BBA & 0.9100 & 27.3000 & 0.0937 & 49.9454 \\  & BBA-IF1 & 0.9097 & 27.0333 & 0.0939 & 42.1371 \\ SonarEW & BBA-IF2 & 0.9100 & 27.3000 & 0.0937 & 44.0751 \\  & BBA-IF3 & 0.9105 & **26.7000** & 0.0931 & **41.8531** \\  & EBBA & **0.9117** & 27.0667 & **0.0919** & 42.8189 \\  & BBA & 0.7379 & 10.5000 & 0.2643 & 46.5456 \\  & BBA-IF1 & 0.7393 & 10.2333 & 0.2628 & 38.7934 \\ SpectEW & BBA-IF2 & 0.7393 & **10.2000** & 0.2628 & 40.4760 \\  & BBA-IF3 & 0.7386 & 10.7000 & 0.2636 & 39.2009 \\  & EBBA & **0.7407** & 10.7000 & **0.2615** & **38.4262** \\  & BBA & 0.8493 & 8.8667 & 0.1590 & 97.9119 \\  & BBA-IF1 & 0.8493 & 8.8667 & 0.1590 & 86.5623 \\ tic-tac-toe & BBA-IF2 & **0.8521** & **9.0000** & **0.1564** & 89.9898 \\  & BBA-IF3 & **0.8521** & **9.0000** & **0.1564** & 86.5650 \\  & EBBA & **0.8521** & **9.0000** & **0.1564** & **84.4753** \\  & BBA & **0.9519** & 5.2000 & **0.0509** & 46.4947 \\  & BBA-IF1 & 0.9518 & 5.3667 & 0.0511 & 39.7080 \\ Vote & BBA-IF2 & 0.9516 & **5.1000** & 0.0511 & 41.6823 \\  & BBA-IF3 & 0.9513 & 5.4333 & 0.0516 & 40.1654 \\  & EBBA & 0.9513 & 5.4000 & 0.0516 & **38.9119** \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Optimization results achieved by various EBBA versions. (The best values are highlighted in bold). Figure 2: Convergence rates achieved by various algorithms. Figure 3: Convergence rates obtained by different EBBA versions.