Motivated by the previous study by Rupp et al. Phys. Rev. Lett, 108, 058301, we implement an improved Kernel Ridge Regression (KRR) model trained on the QM7 dataset and provide a comprehensive evaluation of its applicability. The model is further applied to predict the stability difference between the cis- and trans-isomers of 1,2-dichloroethylene. The accuracy of our model is comparable to that of density functional theory (DFT) calculations, achieving a mean absolute error (MAE) of approximately 4.4 kcal/mol on QM7 dataset. Our findings suggest that, although the KRR model is well established, its performance and transferability can be substantially enhanced through careful feature engineering.
Lee et al. (Wed,) studied this question.