We even tested a random sampling of 0.25k data from the worst-performing systems (e.g., with error threshold > 1 kcal/mol) and continued training the NN model from the previous step (i.e., no training from scratch) with no significant differences. We believe the database reduction will not significantly reduce MAEs for systems with similar chemical features. The driving mechanism of cluster formation is hydrogen bonding. The more training data, the more accurate the NN model. However, perhaps no particular outliers introduce hard-tomodel hydrogen bonds or offer a significantly greater improvement when introduced to the training set. In SI-5, we used KRR and tested the active learning on a small database (0.25k).