3D-dervied descriptors will be different for different conformers of the same SMILES string while other descriptors will be identical. To overcome this, each SMILES is assigned a group (G) and the cross-validation is done in a way that ensures unique training and test molecules respectively. Similarly, the predictions of all conformers of each test molecule were considered when evaluating the outputs as implemented in sci-kit learn. The same process was also used for the deep learning method in Chemprop.