1. A method for modelling data based on a dataset, comprising: in a computing system, executing: a training phase, wherein the dataset is applied to a non-stationary Gaussian process kernel in order to optimize the values of a set of hyperparameters associated with the non-stationary Gaussian process kernel, and an evaluation phase in which the dataset and the non-stationary Gaussian process kernel with optimized hyperparameters are used to generate model data, wherein the evaluation phase comprises a nearest neighbor selection operation, and wherein only a selected subset of nearest neighbor data in the dataset is used to generate each corresponding model data.