where m (j) is the molecular descriptor for the j-th configuration and N t is the number of configurations in the training dataset, w j is the regression coefficients. Further, K is the kernel function. In this work, we use the radial basis function (RBF) kernel in the learning algorithms. The RBF kernel is often called the Gaussian kernel, defined as follows