## 4 Results and Discussion
### Global Explanations of Prediction Model Based on SHAP
#### 4.3.1 Feature Importance
This is because both explanatory variables have similar features related to ground saturation, making it unclear which is the primary factor, leading to the perception that liquefaction is more likely to occur farther from a river. In other words, we believe that the model learns terrain features rather than extracting the dominant factors of liquefaction. However, as shown in Figures 5 and 6, the predictive accuracy of the model was high, suggesting that overall feature extraction for liquefaction was being performed successfully. When a model is trained to align with data trends, it can produce good accuracy; however, if the model does not correctly grasp the overall trend of the data, this is referred to as overfitting. Therefore, when conducting factor analysis using machine-learning models, it is necessary to consider the impact of overfitting. Figure 8 shows the contribution of each explanatory variable to the predicted value of the borehole data. Borehole data served as indicators for determining the compactness and strength of the ground, represented by the SPT-N value. This indicator was obtained through standard penetration tests and was crucial for quantitatively determining the amount of ground subsidence caused by liquefaction. Figure 8 shows the feature importance of the SPT-N value at different depths and the summary plot, with SPT-N values greater than 5 m from the surface having a strong impact on the predicted value, and higher SPT-N values (firmer ground) tending to have a smaller contribution (SHAP value). The pore-water pressure generated deep in the ground dissipates towards the surface, but the supply of pore-water pressure to the ground near the surface can cause liquefaction owing to infiltration failure. Therefore, when liquefied ground is near the surface, the pore-water pressure is rapidly dissipated, resulting in only minor ground subsidence; however, more significant ground subsidence occurs as the drainage distance increases. Thus, it appears that the SPT-N value in deeper ground has a relatively significant impact on the predicted value of ground subsidence owing to liquefaction, generally providing a better explanation for the degree of liquefaction. B_Dist was added as a variable indicating that the distance from the borehole, and feature extraction related to the reliability of the ground information  
is thought to have been performed. Borehole data used in this study were obtained from the nearest boreholes. However, if the corresponding mesh was far from the borehole point, data lost credibility, and different SPT-N values were obtained from the actual point instead. Because ground information is important for predicting ground subsidence, the feature was considered highly important. Finally, Figure 9 shows the contribution of each explanatory variable to the predicted value in the geomorphological classification. Categorical variables were converted into quantitative variables through one-hot encoding, with the corresponding category being true and all other categories being false. As confirmed by the feature importance, geomorphological classification, reflecting a high tendency for liquefaction occurrence, occupied the top ranks, suggesting a high impact on the predicted value. Conversely, a low impact of factors on the predicted value suggests that these factors are not related to ground subsidence, with other features having a significant influence. Therefore, the geomorphological classifications with low feature importance in Figure 9 are likely to be geologically stable and less prone to liquefaction. However, the summary plot shows instances with high SHAP values in geomorphological classifications, such as volcanoes and volcanic foot-slopes. In terms of geomorphological classification, liquefaction is less likely to occur in volcanic areas; however, extensive liquefaction is possible when the soil in these areas contains a liquefaction layer or meets the conditions for liquefaction.