Using the sklearn and XGBoost Python packages, we trained the data with 47 variables to build the RF and XGBoost models. The number of decision trees in the fitted RF model was 99, with a maximum tree depth of six trees. As for the fitted XGBoost, the model’s learning rate was 0.3,...