Machine Learning Kernels

MLKernels.jl is a Julia package for Mercer kernel functions (or the covariance functions of Gaussian processes) that are used in the kernel methods of machine learning. This package provides a collection of kernel datatypes for representing kernel functions as well as an efficient set of methods to compute or approximate kernel matrices. The package has no dependencies beyond base Julia.

Installation

The package may be added by running one of the following lines of code:

# Latest stable release in Metadata:
Pkg.add("MLKernels")

# Most up-to-date (not stable):
Pkg.checkout("MLKernels")

# Development (bleeding edge):
Pkg.checkout("MLKernels", "dev")

Getting Started

Documentation on the interface implemented by MLKernels.jl is available under the interface section listed in the table of contents below or on the sidebar:

A listing of the implemented kernel functions and their properties is available on the kernels page and documentation on the theory surrounding kernel functions and the kernel trick is available in the kernel theory section.