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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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
Stability Experimental
Category AI, Classification, Datamining, Statistics
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Uploaded Wed Oct 26 15:35:53 UTC 2011 by SeanHolden
Distributions NixOS:0.1
Downloads 414 total (5 in the last 30 days)
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Status Docs uploaded by user
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For package maintainers and hackage trustees

Readme for HasGP

Readme for HasGP-0.1

The HasGP package for Gaussian process inference in Haskell

Copyright (C) 2011 Sean Holden

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