A noteworthy observation is the emphasis of low-importance features in the regression (linear and logistic) models with the classifier-based (decision tree and random forest) models, and vice versa (Fig ). This reflects the different nature of both types of models, with classifier models dividing the latent space of features into categories that may not be visible to a regression model. ) into single atoms with various bonding states, functional groups, and activating structures of 3 or more carbon atoms.