# Application of Artificial Neural Network to Somatotype Determination
## 3 Results
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Somatotype and ANN Form**} & \multirow{2}{*}{**Statistics**} & \multirow{2}{*}{**ANN**} & \multicolumn{6}{c}{**Omitted Parameter**} \\ \cline{3-10}  & & & **BMI** & **FFM** & **Res** & **Reac** & **RMR** & **TBW** \\ \hline \multirow{5}{*}{Cedo} & & & MLP 6-5-1 & & & & & \\  & R & 0.9350 & 0.8271 & 0.9136 & 0.8335 & 0.7820 & 0.8672 & 0.9275 \\  & RMSE & 0.4529 & 0.7144 & 0.5340 & 0.7077 & 0.8379 & 0.6558 & 0.5128 \\  & \(\chi^{2}\) & 0.4764 & 1.1854 & 0.6622 & 1.1633 & 1.6305 & 0.9988 & 0.6107 \\  & R & 0.8909 & \(-\)0.1128 & 0.7981 & 0.7715 & 0.8572 & 0.8195 & 0.5187 \\  & RMSE & 0.6063 & 1.5257 & 1.0626 & 0.8620 & 0.7013 & 0.7734 & 1.2268 \\  & \(\chi^{2}\) & 0.8536 & 5.4063 & 2.6222 & 1.7259 & 1.1421 & 1.3894 & 3.4957 \\  & & & MLP 6-4-3 & & & & & \\  & R & 0.9060 & 0.1554 & 0.8751 & 0.7742 & 0.8928 & 0.8795 & 0.8967 \\ Endo, Eto, and Meso & RMSE & 0.5906 & 1.5158 & 0.7095 & 0.8997 & 0.6287 & 0.6628 & 0.6334 \\  & \(\chi^{2}\) & 0.4257 & 2.8039 & 0.6143 & 0.9878 & 0.4824 & 0.5361 & 0.4895 \\  & R & 0.8860 & \(-\)0.3453 & 0.8705 & 0.4759 & 0.8607 & 0.8717 & 0.8796 \\ Endo & RMSE & 0.5886 & 1.9957 & 0.8216 & 1.2928 & 0.6483 & 0.6221 & 0.6379 \\  & \(\chi^{2}\) & 0.7558 & 8.6900 & 1.4729 & 3.6465 & 0.9170 & 0.8443 & 0.8879 \\  & R & 0.9463 & 0.8377 & 0.9404 & 0.9381 & 0.9454 & 0.9120 & 0.9447 \\ Eto & RMSE & 0.4809 & 1.0731 & 0.5577 & 0.5159 & 0.4896 & 0.6102 & 0.5106 \\  & \(\chi^{2}\) & 0.5046 & 2.5123 & 0.6786 & 0.5807 & 0.5231 & 0.8124 & 0.5687 \\  & R & 0.8597 & 0.1987 & 0.8472 & 0.8535 & 0.8412 & 0.8290 & 0.8442 \\ Meso & RMSE & 0.6846 & 1.3261 & 0.72402 & 0.7006 & 0.7252 & 0.7473 & 0.7320 \\  & \(\chi^{2}\) & 1.0227 & 3.8368 & 1.1436 & 1.0710 & 1.1474 & 1.2185 & 1.1690 \\  & & MLP 4-4-1 & & & & & & \\  & R & 0.4680 & 0.4680 & - & 0.7178 & 0.7926 & 0.8366 & - \\ Endo & RMSE & 0.6562 & 1.1365 & - & 0.9502 & 0.8898 & 0.7361 & - \\  & \(\chi^{2}\) & 0.6596 & 1.9787 & - & 1.3830 & 1.2128 & 0.8298 & - \\  & R & 0.8293 & 0.6050 & 0.5464 & 0.8066 & - & - & 0.7535 \\ Meso & RMSE & 0.7546 & 1.0929 & 1.1304 & 0.8250 & - & - & 1.1365 \\  & \(\chi^{2}\) & 0.8723 & 1.8298 & 1.9574 & 1.0426 & - & - & 1.9787 \\  & & MLP 2-4-3 & & & & & & \\  & R & 0.8796 & 0.2569 & - & 0.8314 & - & - & - \\ Endo, Eto, and Meso & RMSE & 0.6703 & 1.3463 & - & 0.7745 & - & - & - \\  & \(\chi^{2}\) & 0.5135 & 2.0715 & - & 0.6855 & - & - & - \\  & R & 0.8777 & 0.2924 & - & 0.7316 & - & - & - \\ Endo & RMSE & 0.6091 & 1.2550 & - & 0.8637 & - & - & - \\  & \(\chi^{2}\) & 0.5937 & 2.5200 & - & 1.1936 & - & - & - \\  & R & 0.9092 & 0.0436 & - & 0.9078 & - & - & - \\ Eto & RMSE & 0.6195 & 1.4715 & - & 0.6230 & - & - & - \\  & \(\chi^{2}\)greatest impact on the Endo somatotype. The Reac (the greatest R = 0.86, the lowest errors: RMSE = 0.70 and \(\chi^{2}\) = 1.14) and RMR (R = 0.82, RMSE = 0.77, \(\chi^{2}\) = 1.39) have the lowest impact, while in turn: BMI (R = \(-\)0.11, the greatest errors: RMSE = 1.53 and \(\chi^{2}\) = 5.41), TBW, FFM and Res have the greatest impact on the Meso somatotype values. The ANN for determining all somatotypes (MLP 6-4-3) is characterized by the fact that TBW and Reac have the lowest impact on obtained somatotypes (the highest R values of 0.90 and 0.89, respectively, the lowest RMSE = 0.63 and \(\chi^{2}\) of 0.50 and 0.48, respectively) and next RMR and FFM while the highest impact has the BMI (R = 0.16, the RMSE = 1.52 and \(\chi^{2}\) = 2.80) and Res. For the Endo somatotype determined from MLP 6-4-3, as for all somatotypes, Res has a large (2 in order, after BMI) impact (R = 0.48, RMSE = 1.29, \(\chi^{2}\) = 3.65). For the Ecto somatotype, Res has a large impact (R = 0.94, RMSE = 0.52, \(\chi^{2}\) = 0.58): third in order after BMI and RMR (R = 0.91, RMSE = 0.61, \(\chi^{2}\) = 0.81), whereas for the Meso somatotype the effect of Res is similar to other parameters.