HasGP-0.1: A Haskell library for inference using Gaussian processes

HasGP-0.1: A Haskell library for inference using Gaussian processes

A Haskell library implementing algorithms for supervised learning, roughly corresponding to chapters 1 to 5 of Gaussian Processes for Machine Learning by Carl Rasmussen and Christopher Williams, The MIT Press 2006. In particular, algorithms are provides for regression and for two-class classification using either the Laplace or EP approximation.

Modules