Even though the use of a larger number of descriptors could provide more information about solvents (for better differentiation), the concept of "plethora of descriptors" 30 comes at the cost of sampling from high dimensional space and potentially introducing (reaction-) irrelevant descriptors. Dimensionality reduction techniques, such as Principal Component Analysis (PCA) or an Autoencoder, could reduce the descriptor space, but with the risk of losing solvability and reaction-relevant descriptors.