for the XGB (FNN, XGB-FNN) model, which is larger than the deviations with the activation energy as a descriptor, which are mostly lower than 100%. For the reactions between alkanes and O (the third column), the deviations for the XGB model are largely smaller than 100% with the similarity as a descriptor while they are mostly in between 50% and 150% when using the activation energy as one of the descriptors. For the FNN and XGB-FNN models, most of the deviations with the similarity as a descriptor are slightly larger than those with the activation energy as a descriptor. Overall, all three machine learning models provide reasonable descriptions of the thermal rate constants and the performance of the activation energy is slightly better than that of the similarity.