The HasGP package
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.
Properties
| Version | 0.1 |
|---|---|
| Dependencies | base (4.*), haskell98 (1.*), hmatrix (0.12.*), hmatrix-special (0.1.*), mtl (2.*), parsec (3.*), random (1.*) |
| 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 |
| Upload date | Wed Oct 26 15:35:53 UTC 2011 |
| Uploaded by | SeanHolden |
| Built on | ghc-7.2 |
Modules
- HasGP
- Classification
- Covariance
- Data
- Demos
- Likelihood
- Parsers
- Regression
- Support
- Types
Downloads
- HasGP-0.1.tar.gz (Cabal source package)
- package description (included in the package)