The final RegioML model released to users is trained on the entire data set and we expect similar performance for molecules in-sample and out-of-sample for this large dataset. The test-set performance is very similar to the graph-based WLN method developed by Struble et al. 8 though the comparison is complicated by the possibility that some of the test and out-of-sample molecules are used to train WLN. RegioML out-performs our physics-based RegioSQM20 method 6 where the precision is only 75%. Even for the out-of-sample dataset, RegioML slightly outperforms RegioSQM20.