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

Version0.1
Change logNone available
Dependenciesbase (==4.*), haskell98 (==1.*), hmatrix (==0.12.*), hmatrix-special (==0.1.*), mtl (==2.*), parsec (==3.*), random (==1.*) [details]
LicenseGPL-3
CopyrightCopyright (C) 2011 Sean Holden
AuthorSean B. Holden
Maintainersbh11@cl.cam.ac.uk
StabilityExperimental
CategoryAI, Classification, Datamining, Statistics
Home pagehttp://www.cl.cam.ac.uk/~sbh11/HasGP
Bug trackersbh11@cl.cam.ac.uk
UploadedWed Oct 26 15:35:53 UTC 2011 by SeanHolden
DistributionsNixOS:0.1
Downloads314 total (13 in last 30 days)
Votes
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StatusDocs uploaded by user
Build status unknown [no reports yet]

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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/