In this work, three different tree-based classifiers were trained including hyperparameter optimization. The two XGBoost models were trained either using 1024-Morgan (radius=2) fingerprints or these same fingerprints concatenated with 15 descriptors calculated using Mordred . These predictors had been previously found to be particularly correlated with taste . The models were evaluated with a multi-class logarithmic loss function, results are given in Table .