We evaluated the different balancing models on the benchmark dataset used in DeepAffinity. The original dataset contains binding data from BindingDB, 20 merged with the amino acid sequence information from UniRef 21 and the SMILES representation of compounds from STITCH. The original dataset consisted on IC50, K i or K d values from 829,033 compoundprotein pairs. We classified the dataset proteins into the main protein families according to the release 2018_09 from Uniprot and restricted our study to proteins of the kinase and G protein-coupled receptors families (separately). Binding activities were in logarithm form, so a threshold of 6 was applied in order to have binary labels for classification (active/inactive).