Gaussian process regression was designed for problems with strictly numeric predictor variables. However, GPR can be used with categorical predictor variables by using one-hot encoding. For example, ...

Our approach is based on Gaussian processes and applies to a wide range of data. In tests, ... Oliphant, T. E. Python for scientific computing. Comput. Sci. Eng. 9, 10 (2007).

Researchers explored the decision-making process of Gaussian process (GP) models, focusing on loss landscapes and hyperparameter optimization. They emphasized the importance of the Matérn kernel ...