Gradient Boosting eXtreme Gradient Boosting (XGBoost) is an ML method that allows both regression and classification. It is based on the Gradient Boosting Decision Tree technique and has been widely applied in the field of data mining. Due to its recently gained popularity over RF in cheminformatics, we used XGBoost as the second baseline method. Similar to RF, XGBoost models were used with a total of 300 estimators and random state set to an integer. The remaining parameters were set to default values.