## 4 Results and Discussion
### Shap Analysis across 49 Features
#### 4.2.3 Results for Quadrant 2  
In Figure 6, it is evident that the 'Number of Micro-Saccade' holds significant importance for predicting emotions in Quadrant 2 of the CMA, which is associated with low arousal and negative valence, indicative of emotions such as sadness, depression, and boredom.  
The Figure 6 shows that higher values of 'Number of Micro-Saccade' positively influence predictions, suggesting that individuals experiencing emotional states such as sadness or depression exhibit more frequent tiny, involuntary eye movements during visual fixation.  
Additionally, an increase in 'Max Micro-Saccade Direction'--which represents the most common orientation or path of a micro-saccade--also positively impacts the model. This implies that not only the frequency but also the specific orientation of micro-saccades is relevant in contexts of sadness or depression.  
Observations from Figure 6 further indicate that higher counts of 'Number of Saccade', 'Max Saccade Duration', and 'Mean Saccade Duration' positively affect the model when predicting emotions characteristic of Quadrant 2. This supports the hypothesis that longer saccade durations are linked to decreased engagement with the environment, which is typical in states of depression, sadness, or boredom.  
Conversely, lower values for 'Mean Blink Duration', 'SD Blink Duration', and 'Max Blink Duration' positively influence the model, suggesting that blinking frequency and duration decrease in these emotional states. However, a higher 'Number of Blink' impacts the model in a positive way, indicating that an increased blinking rate is associated with low arousal and negative emotional states.  
Furthermore, an increase in the 'Number of Fixations' positively impacts model predictions, suggesting that individuals feeling sad or depressed may fixate more frequently, though not necessarily for longer durations. The features 'Mean Fixation Duration' and 'Max Fixation Duration' show average values and do not significantly impact the model, indicating that the duration of fixations may be less indicative of emotional state compared to their frequency.  
These insights demonstrate that eye movement metrics like saccades, micro-saccades, and fixations provide critical indicators of emotional states, particularly in contexts characterized by negative valence and low arousal.  
Figure 6: Summary Plot of the First 10 Features for Quadrant 2. (For a complete view of all 49 features, visit: [[https://doi.org/10.6084/m9.figshare.26130589](https://doi.org/10.6084/m9.figshare.26130589)]([https://doi.org/10.6084/m9.figshare.26130589](https://doi.org/10.6084/m9.figshare.26130589)) (accessed on 10 July 2024)).  
Figure 7 illustrates the impact of feature reduction on the model's performance for Quadrant 2. By utilizing only the top 33 important features instead of the full set of 49, the model achieves an enhanced F1-score of 0.97. Moreover, the model maintains the same F1-score of 0.97 with fewer features--specifically 36, 39, 40, and 42 features--demonstrating that a streamlined feature set can achieve comparable or superior performance compared to using all available features. This finding highlights the potential for optimizing computational efficiency without sacrificing accuracy.