Explainable Machine Learning Models for Predicting Liquefaction-Induced Lateral Spreading

Explainable machine learning models, specifically XGBoost with SHAP analysis, can effectively predict the occurrence of liquefaction-induced lateral spreading by capturing complex soil characteristics and site conditions, while also providing insights into the key factors driving the model's predictions.