## 4 Results and Discussion
### Global Explanations of Prediction Model Based on SHAP
#### 4.3.1 Feature Importance
Geotechnically, when shear stress acts strongly within the ground, the voids in the soil change spatially, causing a rapid increase in pore-water pressure. This theory is derived from [PERSON]'s principle of effective stress and is considered geotechnically sound. Consequently, the contact force between the soil particles decreases, causing the ground to liquefy. Therefore, the high feature importance of the JMA seismic intensity at the engineering bedrock (Ia_min_dI) can be a major cause of liquefaction, owing to the rapid increase in pore-water pressure caused by the seismic motion introduced into the ground. For AVS30, the amplification of the ground is considered to affect the amount of ground subsidence owing to liquefaction. AVS30 represents the average S-wave velocity from the surface to 30 m underground, a parameter dependent on ground density and elastic properties. Generally, firmer ground transmits waves faster, whereas looser ground transmits them more slowly; therefore, areas with looser ground are more prone to noticeable subsidence. It is commonly believed that liquefaction is more likely to occur on weak ground, as indicated by AVS30. The factor plot shows that as the AVS30 value increases, the impact on the predicted value (SHAP value) decreases. Thus, there is a negative correlation between AVS30 and the predicted value, with a lower AVS30 indicating a higher likelihood  
Figure 9: The average absolute SHAP values for the 25 explanatory variables in geomorphologic classification and the SHAP values for each instance: (a) Feature importance plot; (b) summary plot. of weaker ground, and therefore, a greater impact on the amount of ground subsidence due to liquefaction. Regarding topographic data, the highest elevation (Max_Elev), steepest slope angle (Max_Slop_Deg), and minimum slope angle (Min_Slop_Deg) are included. The highest elevation indicates the highest point within a mesh; however, most liquefaction phenomena occur in flat or low-lying areas. This is believed to be influenced by the groundwater level, which is an important factor in the occurrence of liquefaction. Elevation exhibits an inverse relationship with depth below the surface relative to sea level; greater elevation corresponds to reduced ground saturation due to increased depth. Thus, it seems likely that the higher the maximum elevation, the lower the probability of liquefaction. The summary plot shows no clear correlation, but a trend is observed in which the higher the elevation, the smaller the impact on the predicted value. The distance to the coast (Coast_Dist), river (River_Dist), and HAND, were considered. These explanatory variables represent the linear distance from the mesh centroid to the nearest coastline and river, and the relative height from the nearest river, respectively, adding information related to the degree of ground saturation. The impact of each variable on the predicted value was lower than that of the seismic motion and topographic data, confirming a minor impact on the predicted value. The summary plot shows little correlation between the explanatory variables and the predicted value, but it indicates that the farther the distance from the centroid to the river, the more significant the ground subsidence due to liquefaction. This result suggests that the degree of ground saturation does not depend on distance, implying that other factors are at play. Coast and river distances represent the distances from water bodies with high similarity as explanatory variables. Generally, meshes closer to the coast have higher ground saturation because of this explanatory variable. However, meshes close to the coast but far from a river may be incorrectly determined by the learning model as having significant ground subsidence due to liquefaction, despite the strong influence of coastal distance, because they are far from a river.