Results of the five classification and five regression tasks. (a and b) The comparison between our FPs (ours), autoencoder FPs (auto), and circular 2D FPs (ECFP, nine parameter settings). For circular 2D fingerprints, we choose the best fingerprint among the nine parameter settings for each task as the final result. These three fingerprints achieved the best results in 3, 4, and 3 tasks, respectively. (c,d) The comparison between the fingerprints from pretrained model C, model CP, and model CPZ. These three fingerprints produced the best performance on 7, 2, and 1 tasks of 10 tasks, respectively. All the results were generated by the best machine learning model among GBDT, RF, and SVM.