## 3 Results
\begin{table}
\begin{tabular}{l c c c c c c c c} \hline \hline  & \multicolumn{4}{c}{**TRAINING SET**} \\ \hline  & \multicolumn{2}{c}{**ACCURACY**} & \multicolumn{2}{c}{**SENSITIVITY**} & \multicolumn{2}{c}{**SPECIFICITY**} & \multicolumn{2}{c}{**PRECISION**} \\
**LESION** & \multicolumn{2}{c}{**MEAN**} & \(\pm\)**1 SD** & \multicolumn{2}{c}{**MEAN**} & \(\pm\)**1 SD** & \multicolumn{2}{c}{**MEAN**} & \(\pm\)**1 SD** \\ \hline BCC & 0.997931 & 0.000475 & 0.991772 & 0.002502 & 0.998815 & 0.0004 & 0.99175 & 0.002773 \\ SCC & 0.998225 & 0.000515 & 0.9958 & 0.00246 & 0.998571 & 0.000366 & 0.990031 & 0.002564 \\ MEL & 0.998585 & 0.000376 & 0.995069 & 0.002159 & 0.999085 & 0.000309 & 0.993581 & 0.002148 \\ AK & 0.9978757 & 0.000469 & 0.98977 & 0.002736 & 0.99901 & 0.000418 & 0.993046 & 0.002911 \\ BKL & 0.9979551 & 0.000604 & 0.99258 & 0.003565 & 0.998719 & 0.000419 & 0.991067 & 0.002932 \\ DF & 0.998488 & 0.00042 & 0.993927 & 0.003042 & 0.99923 & 0.000292 & 0.994617 & 0.0020215 \\ NV & 0.998321 & 0.000412 & 0.99141 & 0.002184 & 0.999311 & 0.00323 & 0.995173 & 0.002237 \\ VASC & 0.999768 & 0.000158 & 0.998817 & 0.001053 & 0.999903 & 0.000108 & 0.99932 & 0.000756 \\ MEAN \(\pm\) 1 SD & 0.998391 & 0.000617 & 0.993565 & 0.002882 & 0.99908 & 0.000417 & 0.993573 & 0.002906 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Results for cubic SVM. \begin{table}
\begin{tabular}{l c c c c c c c c} \hline \hline  & \multicolumn{4}{c}{**TRAINING SET**} \\ \hline  & \multicolumn{2}{c}{**ACCURACY**} & \multicolumn{2}{c}{**SENSITIVITY**} & \multicolumn{2}{c}{**SPECIFICITY**} & \multicolumn{2}{c}{**PRECISION**} \\
**LESION** & \multicolumn{2}{c}{**MEAN**} & \(\pm\)**1 SD** & \multicolumn{2}{c}{**MEAN**} & \(\pm\)**1 SD** & \multicolumn{2}{c}{**MEAN**} & \(\pm\)**1 SD** \\ \hline BCC & 0.977502 & 0.003381 & 0.93541 & 0.015774 & 0.98365 & 0.003091 & 0.89323 & 0.018677 \\ SCC & 0.979337 & 0.002892 & 0.921498 & 0.020366 & 0.987716 & 0.0027 & 0.915755 & 0.017457 \\ MEL & 0.976551 & 0.003395 & 0.858984 & 0.024565 & 0.993301 & 0.00136 & 0.947996 & 0.010845 \\ AK & 0.983243 & 0.002995 & 0.919326 & 0.013777 & 0.093147 & 0.002206 & 0.949931 & 0.015829 \\ BKL & 0.978023 & 0.003674 & 0.893106 & 0.022957 & 0.990187 & 0.001856 & 0.928795 & 0.012963 \\ DF & 0.991078 & 0.001802 & 0.947692 & 0.011963 & 0.997261 & 0.001098 & 0.979965 & 0.008013 \\ NV & 0.966044 & 0.004155 & 0.952837 & 0.010116 & 0.967897 & 0.005143 & 0.807599 & 0.024077 \\ VASC & 0.993671 & 0.001883 & 0.959445 & 0.013131 & 0.998526 & 0.000779 & 0.989305 & 0.005602 \\ MEAN \(\pm\) 1 SD & 0.980681 & 0.008731 & 0.922862 & 0.033929 & 0.988961 & 0.009796 & 0.926572 & 0.057544 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Results for fine k-NN. \begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline  & \multicolumn{4}{c}{**TRAINING SET**} \\ \hline  & \multicolumn{2}{c}{**ACCURACY**} & \multicolumn{2}{c}{**SENSITIVITY**} & \multicolumn{2}{c}{**SPECIFICITY**} & \multicolumn{2}{c}{**PRECISION**} \\
**LESION** & \multicolumn{2}{c}{**MEAN**} & \(\pm\)**1 SD** & \multicolumn{2}{c}{**MEAN**} & \(\pm\)**1 SD** & \multicolumn{2}{c}{**MEAN**} & \(\pm\)**1 SD** \\ \hline BCC & 0.977502 & 0.003381 & 0.93541 & 0.015774 & 0.98365 & 0.003091 & 0.89323 & 0.018677 \\ SCC & 0.979337 & 0.002892 & 0.921498 & 0.020366 & 0.987716 & 0.0027 & 0.915755 & 0.017457 \\ MEL & 0.976551 & 0.003395 & 0.858984 & 0.024565 & 0.993301 & 0.00136 & 0.947996 & 0.010845 \\ AK & 0.983243 & 0.002995 & 0.913926 & 0.013777 & 0.993147 & 0.002206 & 0.949931 & 0.015829 \\ BKL & 0.978023 & 0.003674 & 0.893106 & 0.022957 & 0.990187 & 0.001856 & 0.928795 & 0.012963 \\ DF & 0.991078 & 0.001802 & 0.947692 & 0.011963 & 0.997261 & 0.001098 & 0.979965 & 0.008013 \\ NV & 0.966044 & 0.004155 & 0.952837 & 0.010116 & 0.967897 & 0.005143 & 0.807599 & 0.024077 \\ VASC & 0.993671 & 0.001883 & 0.959445 & 0.013131 & 0.998526 & 0.000779 & 0.989305 & 0.005602 \\ MEAN \(\pm\) 1 SD & 0.980681 & 0.008731 & 0.922862 & 0.033929 & 0.988961 & 0.009796 & 0.926572 & 0.057544 \\ \hline \hline \end{tabular}
\end{table}