# Evaluation of Emotions from Brain Signals on 3D VAD Space via Artificial Intelligence Techniques
## 4 Discussion
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Sep. Level**} & \multirow{2}{*}{**Class**} & \multicolumn{4}{c}{**CCI (\%)**} & \multicolumn{4}{c}{**F1 Score (\%)**} & \multicolumn{4}{c}{**MCC (\%)**} \\ \cline{3-10}  & & **Value** & **Classifier \({}^{*}\)** & **Segment** & **Value** & **Classifier** & **Segment** & **Value** & **Classifier** & **Segment** \\ \hline \multirow{4}{*}{(5)} & A\&G & 81.71 & RSS & V & 80.5 & RSS & V & 54.9 & RSS & V \\  & B\&H & 81.98 & RSS & V & 81.9 & RSS & V & 63.8 & RSS & V \\  & D\&F & 85.68 & RF & V & 85.5 & RF & V & 69.2 & RF & V \\  & C\&E & 86.84 & RSS & V & 86.8 & RSS & V & 72.9 & RSS & V \\ \hline \multirow{4}{*}{(4–6)} & A\&G & 85.13 & RSS & V & 84.3 & RSS & V & 62.3 & RSS & V \\  & B\&H & 91.01 & OF & V & 90.9 & OF & V & 80.7 & OF & V \\  & D\&F & 92.35 & RF & V & 92.3 & RF & V & 82.9 & RF & V \\  & C\&E & 96.97 & FURIA & IV & 97.0 & FURIA & IV & 93.9 & FURIA & IV \\ \hline \multirow{4}{*}{(3–7)} & A\&G & 90.08 & RSS & V & 89.6 & RSS & V & 72.2 & RSS & V \\  & B\&H & 96.03 & RC & V & 95.9 & RC & V & 85.2 & RC & V \\  & D\&F & 91.32 & RSS & V & 91.4 & RSS & V & 81.3 & RSS & V \\ \hline \multirow{4}{*}{(4-5-5.5)} & C\&E & 98.94 & IBk & III & 98.9 & IBk & III & 97.9 & IBk & III \\ \cline{1-1} \cline{2-10}  & & & & & & & & & & \\ \hline \hline \end{tabular}  
* FURA: Fuzzy Unordered Rule Induction Algorithm; IBk: Instance-Based Learning (it is a K-Nearest Neighbor classifier); OF: Optimized Forest; RC: Random Committee; RF: Random Forest; RSS: Random Subspace; SMO: Sequential Minimum Optimization.  
\end{table} 
Table 3: Best CCI, MCC values, and F1 Scores (%) among Segments III, IV, and V for the cross-comparisons of VAD space. from the middle point (5), the accuracy values increase in general, which can also be seen in both of the tables. For the A&G classes, which compare happy, joyful, excited, and powerful and sad, depressed, and feeble emotions, for the class separation levels 5 and 4-6, accuracy rates of 88.62% and 91.45% (CCI) are obtained, respectively, with the RF classifier and Seg V. For the 3-7 class separation level, an accuracy rate of 95.58% (CCI) is obtained for the SMO classifier according to the data-balanced results. For the B&H classes, which compare relaxed, leisurely, and satisfied and fear, pain, and guilt emotions, for the class separation levels 5 and 4-6, accuracy rates of 82.60% and 93.37% (CCI) are obtained, respectively, with the OF classifier and Seg V. For the 3-7 class separation level, an accuracy rate of 100% (CCI) is obtained with both RF and OF classifiers according to the data-balanced results. For the D&F classes, which compare angry, hate, and disgusted and protected, humble, and reverent emotions, for the class separation level 5, an accuracy rate of 89.94% (CCI) is obtained with the OF classifier and Seg V, and for the class separation level 4-6, an accuracy rate of 94.76% (CCI) is obtained for all IBk, SMO (Seg IV), and RC (Seg III and V) classifiers. For the class separation level 3-7, an accuracy rate of 95.05% (CCI) is obtained for the SMO classifier and Seg V according to the data-balanced results. For the C&E classes, which compare disdainful and unconcerned and impressed, surprised, and thankful emotions, for the class separation level 5, an accuracy rate of 90.31% (CCI) is obtained with the OF classifier and Seg V, and for the class separation level 4-6, an accuracy rate of 97.92% (CCI) is obtained for the RC classifier and Seg III. For the class separation level 4.5-5.5, an accuracy rate of 97.92% (CCI) is obtained for the IBk classifier and Seg III according to the data-balanced results. The best accuracy result in this study is for the C&E comparison for the unbalanced data (98.94% CCI with IBk classifier and Seg III for the 4.5-5.5 class separation). For the C&E comparison and the class separation level 4-6, an accuracy rate of 96.97% (CCI) is obtained with the FURIA classifier and Seg IV according to the unbalanced data results.