## 3 Results
### Feature Importance
* Distinction between Red (ULS) and Black (Collapse): As can be seen from the left part of Figure 4a, the most crucial factor overall for the Collapse Limit State is the presence of soft storeys and/or short columns, with a weight of approximately 18%. Figure 4: Feature importance coefficients \(\overline{\lambda}_{i}\) as defined in (6) for the three damage label pairs: (a) (Red, Black), (b) (Yellow, Red), and (c) (Green, Yellow). The presence of regular infill panel walls, however, has an almost equal in magnitude, but a positive effect, which is why the corresponding bar in the figure is hatched. This is an important feature that helped prevent structures that crossed the ULS to cross the CLS as well. Finally, the absence of design seismic codes, the number of storeys in the structure, and the presence of an irregular plan all play import roles for this damage threshold. The right part of this feature displays an important distinction, as the absence of design seismic codes is now the dominant feature, even if only slightly. This can be explained in the following way. The absence of design seismic codes feature is indeed a crucial factor, as is well known in the literature, and the model assigns high SHAP values to it. However, not many structures were affected by this feature. Of the 452 structures in our dataset, only 26 lacked a design seismic code. Of these, 20 (77%) crossed the ULS, and 19 of those (95%) crossed the CLS as well. Thus, by taking the squares of the SHAP values, as per the right figure of Figure 4a, we assign more weight to these extreme SHAP values even though they pertained to only a limited number of cases. It is important to note that there is not a noteworthy distinction in the other factors, such as soft storeys/short columns, regularity of the infill panel walls, or structure height, between the left and right subfigures of Figure 4a, as the corresponding SHAP values are more balanced. * Distinction between Yellow (SLS) and Red (ULS): As can be seen from Figure 4b, the most important features by far are the presence of soft storeys and/or short columns as well as the presence of regular infill wall panels. Soft storeys/short columns had a detrimental effect, accounting for approximately 30% of the total. On the other hand, regular infill wall panels had a beneficial effect with approximately equal magnitude. This is in agreement with the established engineering literature, as bricks walls help to reduce storey drift, and consequently decrease the overall degree of damage. The absence of design seismic codes did not play an important role in this case, as most structures that displayed this feature crossed the CLS as well, as mentioned above. Pounding, on the other hand, had a contribution of approximately 15%. The height of the structure and potential preexisting poor condition accounted for 7-8% each. Out of the thirteen total features, these five combined to account for approximately 85% of the total in the model's predictions. Finally, we note that in this case the SHAP values are balanced, as the left and right subfigures, using \(\mathcal{L}_{1}\) and \(\mathcal{L}_{2}\), respectively, show minimal differences. * Distinction between Green (minimal to no damage) and Yellow (SLS): Finally, the results for the distinction between structures that crossed the SLS (Yellow) and those that suffered minimal to no damage are shown in Figure 4c. It can be seen that the most important factors here are the existence and type of design seismic codes, each of which account for approximately 20% of the total. This is in agreement with the post-1985 Greek seismic codes, which enforce lower damage degrees for the same earthquake design. Regular infill panel walls, soft storeys and/or short columns, and the presence of adjacent structures that could lead to bounding were relevant here, although the magnitude of their effect was only approximately 10%.