Extracting spatial effects from machine learning model using local interpretation method: An example of SHAP and XGBoost

Extracting spatial effects from machine learning model using local interpretation method: An example of SHAP and XGBoost Machine learning and artificial intelligence (ML/AI), previously considered black box approaches, are becoming more interpretable, as a result of the recent advances in eXplainable AI (XAI). In particular, local interpretation methods such as SHAP (SHapley Additive exPlanations) offer the opportunity to flexibly model, interpret and visualise complex geographical phenomena an...