GPy.kern package¶

Introduction¶

In terms of Gaussian Processes, a kernel is a function that specifies the degree of similarity between variables given their relative positions in parameter space. If known variables x and x’ are close together then observed variables y and y’ may also be similar, depending on the kernel function and its parameters. Note: this may be too simple a definition for the broad range of kernels available in :py:class:GPy.

GPy.kern.src.kern.Kern is a generic kernel object inherited by more specific, end-user kernels used in models. It provides methods that specific kernels should generally have such as GPy.kern.src.kern.Kern.K to compute the value of the kernel, GPy.kern.src.kern.Kern.add to combine kernels and numerous functions providing information on kernel gradients.

There are several inherited types of kernel that provide a basis for specific end user kernels:

e.g. the archetype GPy.kern.RBF does not inherit directly from GPy.kern.src.kern.Kern, but from GPy.kern.src.stationary.