We used the PDBbind 2018 Refined Set 10 of high-quality protein-ligand structures and binding affinities as our source of training data. This consists of 4,463 crystal structures of protein-ligand complexes from the PDB 20 with experimentally-determined binding affinity values. For our training set we selected all the structures in the PDBbind 2018 Refined Set, but excluded 481 structures for which either the docking failed or features could not be computed; we also excluded any structures that were also present in the PDBbind Test Set (described below). This resulted in a training set of 3,752 high quality protein-ligand complexes with corresponding binding affinity data, which we refer to as the "PDBbind Training Set". We used the PDBbind 2018 Refined Set rather than the larger PDBbind 2018 General Set 10 for two reasons. Firstly, structures in the Refined Set are subject to strict quality controls, including a resolution of 2.5 Å or better and no missing side chains, reducing the risk of errors in the docking results that might be introduced by the use of inaccurate crystal structures. Secondly, while several authors have reported improved performance on the PDBbind Core Sets when training on the larger General Set instead of the Refined Set, we observed previously that this can be attributed to increased representation of the Core Set proteins in the training set: when proteins with high sequence identity to those in the test set were excluded from the training set, there was little difference in performance between training on the General Set and training on the Refined Set.