The HasGP package

[Tags:gpl, library]

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.


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Properties

Versions 0.1
Dependencies base (==4.*), haskell98 (==1.*), hmatrix (==0.12.*), hmatrix-special (==0.1.*), mtl (==2.*), parsec (==3.*), random (==1.*) [details]
License GPL-3
Copyright Copyright (C) 2011 Sean Holden
Author Sean B. Holden
Maintainer sbh11@cl.cam.ac.uk
Stability Experimental
Category AI, Classification, Datamining, Statistics
Home page http://www.cl.cam.ac.uk/~sbh11/HasGP
Bug tracker sbh11@cl.cam.ac.uk
Uploaded Wed Oct 26 15:35:53 UTC 2011 by SeanHolden
Distributions NixOS:0.1
Downloads 404 total (4 in the last 30 days)
Votes
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Status Docs uploaded by user
Build status unknown [no reports yet]

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Readme for HasGP

Readme for HasGP-0.1

The HasGP package for Gaussian process inference in Haskell
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Copyright (C) 2011 Sean Holden sbh11@cl.cam.ac.uk

For a detailed description of how to install, use and modify this code 
please download the User Manual from the project site at:

http://www.cl.cam.ac.uk/~sbh11/HasGP/