What is this repository for?

  • This is a Gaussian Process multi-class classification toolbox, in which Laplace Approximation is used for inference and maximising marginal likelihood is adapted to optimise the hyper-parameters of kernel functions.

  • Version 1.01

Who need this toolbox?

  • This toolbox is design for those who want to solve multi-class classification and require the full predictive probabilities.

How do I get set up?

(1) As this toolbox supports all kernels provided by GPML, you need to add GPML's toolbox ( to the path.

(2) run startup.m (GPML) to setup environment for GPML's toolbox.

(3) run demo.m (multi-class GPC)

Contribution guidelines

This toolbox is mainly following GPML (Book: Gaussian Process for Machine Learning). We implement GP multi-class classification because it is not provided by GPML's toolbox.