All three r i regression models obtained an accuracy of 81% for the training set and, for the test set, the amide, UoA, and cocamide models had an accuracy of 68%, 70%, and 67%, respectively. The r i regression models were built and optimized for the amide, UoA and cocamide series. Grid optimization of each of these models showed that the number of trees did not influence the performance of the model (Figures and). Therefore, to keep the model light, 200 trees were selected. As for the minimum number of samples per leaf, 8 was found to be the optimum, based on the training and cross-validation accuracy.