ρ P = 0.738). Similarly, training on multiple copies of the pose ranked highest by Smina does significantly affect performance, indicating that the models are not adversely affected by redundancy in the training data. These results, together with those in Table and Table , suggest that when using Random Forest for protein-ligand binding affinity prediction, it is important for the model to see examples of docked poses of varying quality, but using a variety of example poses for each complex is not necessary.