## 3 Results
### Machine Learning Classification
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & \multicolumn{5}{c}{**Performance Time (s)**} \\ \cline{2-6}
**Classification Model** & \multicolumn{5}{c}{**Number of Significant Bands**} \\ \cline{2-6}  & **35** & **18** & **9** & **14** & **11** \\ \hline Fine tree & 5.0538 & 4.6277 & 1.2873 & 3.6890 & 3.8240 \\ Medium tree & 4.3907 & 4.2772 & 0.9609 & 3.2645 & 3.3773 \\ Coarse tree & 3.9659 & 4.0446 & 0.8531 & 3.0669 & 3.2237 \\ Linear discriminant & 5.5868 & 3.6876 & 0.7478 & 2.7450 & 2.9791 \\ Quadratic discriminant & 5.3982 & 5.3332 & 0.6290 & 4.3591 & 2.7304 \\ Logistic regression & 6.5610 & 5.1549 & 1.3870 & 4.1698 & 4.3726 \\ Gaussian naïve Bayes & 4.4120 & 4.7064 & 0.4503 & 3.7530 & 3.9366 \\ Kernel naïve Bayes & 8.7138 & 6.6702 & 2.6167 & 4.8786 & 4.6418 \\ Linear SVM & 5.1192 & 4.0248 & 1.2056 & 3.5172 & 3.7279 \\ Quadratic SVM & 12.8810 & 15.0320 & 15.1990 & 11.1230 & 11.6320 \\ Cubic SVM & 30.8420 & 36.4900 & 33.1880 & 34.1180 & 35.0530 \\ Fine Gaussian SVM & 6.1060 & 4.6642 & 1.0061 & 3.8789 & 3.0490 \\ Medium Gaussian SVM & 4.8147 & 4.5799 & 0.8960 & 3.7307 & 2.9310 \\ Coarse Gaussian SVM & 5.9675 & 5.5084 & 1.7124 & 4.1013 & 4.2087 \\ Fine kNN & 6.7865 & 4.9865 & 0.5287 & 3.5970 & 3.7909 \\ Medium kNN & 5.7937 & 4.8772 & 1.1323 & 3.9551 & 3.6686 \\ Coarse kNN & 6.1868 & 5.3351 & 1.0433 & 3.8722 & 4.0413 \\ Cosine kNN & 6.0353 & 5.2496 & 0.9635 & 4.3031 & 3.9559 \\ Cubic kNN & 8.9532 & 6.1620 & 1.3550 & 4.8110 & 5.2101 \\ Weighted kNN & 6.4390 & 5.6440 & 0.8320 & 4.7278 & 4.1607 \\ Bagged trees & 11.2750 & 9.1523 & 4.2469 & 8.2750 & 7.7564 \\ Subspace discriminant & 13.2520 & 9.9335 & 4.7204 & 9.0717 & 8.4402 \\ Subspace kNN & 14.1990 & 10.8960 & 4.6275 & 9.4566 & 9.3989 \\ \hline \hline \end{tabular} Note: (*) significant at the \(p\leq 0.05\).  
\end{table} 
Table 7: Performance time of models developed using the significant bands. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & \multicolumn{5}{c}{**\(p\)-Value**} \\ \cline{2-6}
**Classification Model** & \multicolumn{5}{c}{**Number of Significant Bands**} \\ \cline{2-6}  & **35** & **18** & **9** & **14** & **11** \\ \hline Fine tree & 0.0291 * & 0.2636 & 0.1356 & 0.8312 & 0.6625 \\ Medium tree & 0.0809 & 0.4795 & 0.3588 & 0.8231 & 1.0000 \\ Coarse tree & 0.6056 & 0.7893 & 0.6276 & 0.6276 & 1.0000 \\ Linear discriminant & 0.8445 & 1.0000 & 0.2386 & 0.5023 & 0.3588 \\ Quadratic discriminant & 0.1042 & 0.7194 & 0.7103 & 1.0000 & 0.8383 \\ Logistic regression & 0.1698 & 0.4795 & 0.6767 & 0.3588 & 0.8231 \\ Gaussian naïve Bayes & 0.6056 & 0.6056 & 0.2864 & 4.4795 & 0.3827 \\ Kernel naïve Bayes & 0.7893 & 0.7893 & 0.6625 & 1.0000 & 0.8137 \\ Linear SVM & 0.7893 & 1.0000 & 0.8137 & 1.0000 & 0.7893 \\ Quadratic SVM & 1.0000 & 0.8137 & 0.6464 & 0.8137 & 0.7893 \\ Cubic SVM & 0.4533 & 0.6767 & 0.0000 * & 0.8551 & 0.6276 \\ Fine Gaussian SVM & 0.7893 & 1.0000 & 0.8026 & 0.7893 & 0.8026 \\ Medium Gaussian SVM & 0.7893 & 0.7893 & 1.0000 & 0.7893 & 0.6056 \\ Coarse Gaussian SVM & 0.7893 & 0.7893 & 0.3017 & 0.4533 & 0.4533 \\ Fine kNN & 0.0455 * & 0.2109 & 0.2864 & 0.8231 & 0.2864 \\ Medium kNN & 0.7893 & 1.0000 & 1.0000 & 0.7893 & 1.0000 \\ Coarse kNN & 0.7893 & 0.7893 & 0.8026 & 1.0000 & 0.6056 \\ Cosine kNN & 0.0809 & 0.1175 & 0.1904 & 0.1175 & 0.1687 \\ Cubic kNN & 0.7893 & 1.0000 & 1.0000 & 0.7893 & 1.0000 \\ Weighted kNN & 0.7893 & 1.0000 & 0.8026 & 1.0000 & 0.8026 \\ Bagged trees & 1.0000 & 0.4533 & 0.8026 & 0.8026 & 0.8026 \\ Subspace discriminant & 0.6625 & 0.6464 & 0.0990 & 0.3320 & 0.4795 \\ Subspace kNN & 0.0776 & 0.5023 & 0.2636 & 0.8231 & 0.1904 \\ \hline \hline \end{tabular} Note: (*) significant at the \(p\leq 0.05\).  
\end{table} 
Table 8: \(P\)-values of [PERSON]’s test for each model of each significant bands.