We trained a gradient-boosted tree model on data featurized with the raw robocrystallographer features. We did 80/20 train test split for this. Table shows the comparison of the MAE scores: This comparison shows that, our features are giving better results than the raw Robocrystallographer features for three of the four properties. It suggests that, our features are representing the data in a way that is easier for the model to learn from than the original features.