## 5 Results and Discussion of Findings
### Comparative Analysis of Fitness and Cost Functions
Figure 6: Graph-based comparative analysis of the cost function values obtained for all binary optimization methods on (**a**) Zoo; (**b**) Vote; (**c**) Wine; (**d**) Sonar; (**e**) Tic-tac-toe; (**f**) M-of-n; (**g**) Ionosphere; (**h**) Exactly; (**i**) Exactly; (**j**) HeatEW; (**k**) CongressEW; (**l**) Lymphography; (**m**) Colon; (**n**) BreastEW; and (**o**) SpectEW datasets. The performance of the algorithms on the Zoo dataset were as follows: the cost values range for BIEOSA was 0.50-0.52, BSNDO 0.64-0.65, BDMO 0.75-0.76, BWOA 0.80-0.81, BPSO 0.84-0.85, BGWO 0.74-0.95, and BEOSA 0.99-1.0. The Vote dataset yielded the following results: BWOA 0.80, BGWO 0.75-0.93, BSNDO, BDMO and BEOSA all 0.94, BIEOSA 0.94-0.97, and BPSO 0.98. The Wine dataset results were as follows: BDMO 0.58, BGWO 0.58-0.97, BSNDO 0.7750-0.7799, BWOA 0.81, BEOSA 0.94, BPSO 0.88-0.97, and BIEOSA 0.97. Performance with the sonar dataset was as follows: BDMO was the lowest among all curves at less than 0.55; meanwhile, BSNDO was at 0.76, BIEOSA was 0.78, BWOA was 0.81, BGWO 0.88-0.87, BPSO 0.88-0.91, and BEOSA 0.86-0.93. For the tic-tac-toe dataset performance BGWO outperformed the other methods by running from 0.62-0.82, BDMO was 0.59, BWOA was 0.62, BIEOSA was 0.63, BSNDO was 0.66, BPSO was 0.68, and BEOSA was 0.73. The performance of the algorithms on the M-of-n dataset was as follows: the cost function values for BDMO were just above the 0.50 value, while those of BSNDO were 0.62, BWOA was 0.72, BIEOSA was 0.78, BEOSA was 0.83, BGWO was 0.80-0.84 with its peak at 0.97, and BPSO was 0.92-1.0. The Ionosphere dataset yielded the following results: BGWO began its curve from 0.752 and ended at 0.777, BWOA ran through 0.812, BDMO ran through 0.8125, BIEOSA went from 0.826 to 0.840, BSNDO was above 0.850, the BEOSA curve was just above 0.875, and the BPSO curve started from 0.805 and extended to just above 0.900. The Exactly and Exactly2 datasets yielded the following patterns: the BDMO curves were at 0.577 and 0.45 for Exactly and Exactly2, respectively. The BIEOSA curve was 0.625 with Exactly and ranged from 0.64 to 0.68 on Exactly2, BWOA was 0.635 with Exactly and 0.47 with Exactly2, BSNDO was 0.635 with Exactly and 0.60 on Exactly2, BGWO ranged from 0.650 to 0.635 on Exactly and from 0.75 to 0.70 on Exactly2, BPSO was 0.675 with Exactly and 0.75 with Exactly2, and BEOSA was just below 0 to above 0.76 with Exactly and Exactly2, respectively. The result for HeartEW showed that BWOA and BDMO ranked lowest, with cost function value of around 0.50. BGWO followed, starting at 0.55, peaking at 0.83 and ending at 0.69; BIEOSA was 0.64, BPSO ran from 0.65 to 0.75, and lastly, BEOSA, was above all the other algorithms at 0.78. The CongressEW and Lymphography datasets demonstrated some similarity, with the BSNDO curve at the bottom with 0.62 and 0.52, respectively. This was followed by BDMO, which was at 0.80 and 0.70 with the CongressEW and Lymphography. While the BIEOSA, BWOA and BPSO curves were around 0.95 for the CongressEW dataset, the same algorithms were sparsely plotted with the Lymphography dataset at 0.68, 0.80, and 0.90, respectively. Typically for BGWO, in this case, it started at 0.89 and ended at 0.86 for CongressEW and started at 0.84 and ended at 0.78 with the Lymphography dataset. The BEOSA curve was a 0.875 on the CongressEW dataset and 0.80 on the Lymphography dataset. The algorithm curves showed different performance with the Colon and BreastEW datasets. For instance, where the BWOA algorithm curve was below 0.70 with Colon, it shot up above 0.90 with BreastEW. Additionally, the curve of BSNDO was around 0.85 for the Colon graph but fell below 0.70 with the BreastEW graph. BIEOSA also showed some disparity on Colon, where it crossed the graph close to 0.85; meanwhile, with the BreastEW, it had a better cost value, running close to 0.95. The characteristic of BGWO is that it always zig-zagged its curves, as can be seen with Colon, where it started at 0.92 and ended on the same value, peaking at around 1.0 and dipping to around 0.85.