## 4 Presentation and Discussion of Findings
### Predicted Pseudo-Probability of the Professionals  
The predictive pseudo-probability of level 2 as shown in Figure 2, further confirms the findings of Table 4. Pseudo-probability is the combined likelihood of all random variables [71]. Consequently, predictive pseudo-probability further confirms the classification of the predicted output. Predictive pseudo-probability, there is further confirmation of Table 4 in a graphical format. The predictive \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{3}{*}{**Predictor**} & \multicolumn{8}{c}{**Predicted**} \\ \cline{2-9}  & \multicolumn{4}{c}{**Hidden Layer 1**} & \multicolumn{4}{c}{**Output Layer**} \\ \cline{2-9}  & **H(1:1)** & **H(1:2)** & **H(1:3)** & **H(1:0)** & **H(1:5)** & **H(1:6)** & **QS** & **CPM** \\ \hline \multirow{9}{*}{**Input Layer**} & (Bias) & 0.058 & \(-\)0.064 & 0.266 & 0.452 & 0.350 & 0.184 & \multirow{9}{*}{**Input Layer**} \\  & CFLOW & 0.254 & 0.053 & 0.562 & 0.349 & 0.376 & 0.303 & \\  & HDATA & 0.527 & \(-\)0.144 & \(-\)0.158 & \(-\)0.372 & \(-\)0.261 & 0.195 & \\  & SIMP & 0.196 & 0.253 & \(-\)0.062 & 0.138 & 0.023 & 0.434 & \\  & TCACT & 0.072 & 0.376 & \(-\)0.500 & 0.030 & \(-\)0.382 & 0.456 & \\  & MONLC & 0.341 & 0.564 & 0.151 & 0.078 & 0.077 & \(-\)0.044 & \\  & MONMC & \(-\)0.297 & 0.523 & 0.283 & 0.224 & \(-\)0.322 & 0.606 & \\  & MONEC & \(-\)0.405 & \(-\)0.090 & 0.566 & \(-\)0.339 & \(-\)0.402 & 0.667 & \\  & MONOV & \(-\)0.130 & 0.136 & \(-\)0.098 & 0.196 & 0.326 & \(-\)0.201 & \\  & VARMAN & \(-\)0.272 & \(-\)0.100 & \(-\)0.340 & \(-\)0.322 & \(-\)0.247 & 0.030 & \\  & COSTR & \(-\)0.146 & \(-\)0.342 & \(-\)0.059 & 0.334 & 0.107 & \(-\)0.099 & \\  & INCMILE & \(-\)0.278 & 0.338 & 0.529 & \(-\)0.627 & \(-\)0.388 & 0.275 & \\  & COMPRUN & 0.617 & \(-\)0.223 & \(-\)0.076 & \(-\)0.034 & 0.058 & \(-\)0.413 & \\  & IDCOV & 0.381 & \(-\)0.352 & \(-\)0.189 & 0.233 & 0.074 & 0.294 & \\  & FORCOMP & 0.018 & \(-\)0.104 & 0.117 & \(-\)0.098 & 0.126 & 0.275 & \\  & COSTFOR & \(-\)0.349 & 0.140 & 0.656 & 0.114 & 0.335 & 0.159 & \\  & INTERIMV & 0.160 & 0.445 & 0.546 & 0.017 & 0.132 & \(-\)0.185 & \\  & WORKBUD & 0.627 & 0.574 & \(-\)0.225 & 0.322 & \(-\)0.107 & 0.056 & \\  & PamPL & 0.215 & \(-\)0.567 & 0.285 & \(-\)0.444 & \(-\)0.235 & \(-\)0.069 & \\ \hline \multirow{9}{*}{Hidden Layer 1} & (Bias) & & & & & & 0.555 & 0.030 \\  & H(1:1) & & & & & \(-\)0.494 & 0.367 \\  & H(1:2) & & & & & 0.163 & \(-\)0.294 \\  & H(1:3) & & & & & 0.259 & \(-\)0.198 & \\  & H(1:4) & & & & & 0.527 & \(-\)0.388 & \\  & H(1:5) & & & & & & 0.295 & \(-\)0.229 \\  & H(1:6) & & & & & & 0.034 & 0.638 \\ \hline \hline \end{tabular} (Source: Authors’ compilation, 2020).  
\end{table} 
Table 4: Synaptic parameter estimates for level 2. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Sample** & **Observed** & **QS** & **CPM** & **Percent Correct** \\ \hline Level 1 & & & & \\  & QS & 70 & 7 & 90.90\% \\ Training & CPM & 19 & 39 & 67.20\% \\  & Overall Percent & 65.90\% & 34.10\% & 80.70\% \\ Level 2 & & & & \\  & QS & 68 & 9 & 88.30\% \\ Training & CPM & 38 & 20 & 34.50\% \\  & Overall Percent & 78.50\% & 21.50\% & 65.20\% \\ \hline \hline \end{tabular} (Source: Authors’ compilation, 2020).  
\end{table} 
Table 5: Classification of predicted observed outcome from the multilayer perceptron. pseudo-probability is a confirmation of the correct percentages in Table 4. Figure 3 reveals the blue box to the 'y' axis as values above 0.5. The blue boxes, which are also labelled as 1, represents the QS. This shows that the cases are correctly classified. The classification of 2, which is the CPM shows that the majority of the blue boxes below are below 0.5. The predictive pseudo-probability of level 2 as shown in Figure 2, further confirms the findings of Table 4. The QS predictive percentage have a pseudo-probability which is far above 0.5 for the two categories in blue. Hence, there is a confirmation that the category of the professional output of decision making comes from the QS. This is a good result which must be validated with a holdout sample.