GPR works well with small datasets and generates a metric of confidence of a predicted result, but it's moderately complex and the results are not easily interpretable, says Dr. James McCaffrey of ...

A regression problem is one where the goal is to predict a single numeric value. For example, you might want to predict the price of a house based on its square footage, age, number of bedrooms and ...

Bayesian analysis of constrained Gaussian processes integrates prior knowledge and observed data to model complex functions subject to known restrictions. Constrained Gaussian processes extend ...