Notably, the drug-like subset contained fewer compounds beyond the h * threshold with high prediction errors. For compounds with high leverage, certain descriptors may have a pronounced influence, but the model's predictions remain stable due to their consistency with the trained model. This highlights the thoughtful selection of descriptors, which effec-tively describe both the main distribution and rare data points. Thus, such outliers can be considered "suitable" for the model, even if they lie outside the primary distribution.