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 ...

Gaussian process regression is a sophisticated technique that uses what is called the kernel trick to deal with complex non-linear data, and L2 regularization to avoid model overfitting where a model ...