The large number of RACs, i.e., 150 features (see Sec 2), relative to the number of complexes in our dataset makes it essential to identify the most important features to train transferable models. Identification of these features also provides insight in terms of their graphbased proximity to the metal center as well as their electronic and geometric nature. The identification of these important features can be used to reveal design principles for the discovery of new SCO materials.