Morgan fingerprints are computed using the MolToMorganFP pipeline element from the standardized molecules. The feature vectors are input to scikit-learns machine learning estimators, like RandomForestRegressor. For the sake of simplicity, invalid molecules detected during the assingment of the cluster labels are removed from the data set used for the ML experiments. To account for erroneous molecules occurring during the training and prediction phase, the ErrorFilter and ErrorReinsert elements can be added to the ML pipeline as well.