Project details for pyGPs

Screenshot pyGPs 1.1

by mn - October 8, 2013, 12:35:28 CET [ Project Homepage BibTeX Download ]

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Description:

pyGPs is a Python project for Gaussian process (GP) regression and classification for machine learning.

pyGPs is an object-oriented implemetation of GP regression and classificaion additionally supporting useful routines for the practical use of GPs, such as cross validation functionalities for evaluation as well as basic routines for iterative restarts for the GP hyperparameter optimization.

Note, there is also a procedural implementation of GPs (pyGP_PR) which follows structure and functionality of the gpml matlab implementaion by Carl Edward Rasmussen and Hannes Nickisch (Copyright (c) by Carl Edward Rasmussen and Hannes Nickisch, 2013-01-21). This version can be downloaded via this link: https://github.com/marionmari/pyGP_PR/archive/v1.1.tar.gz.

Future extensions will be designed for pyGPs. pyGP_PR will be maintained as it is now.

Changes to previous version:

pyGPs v1.1 is released. It replaces pyGP_OO and contains substaintal updates in functionality and documentation. pyGP_PR v1.1 is released with substantial documentation updates and renamed (FN -> PR).

BibTeX Entry: Download
URL: Project Homepage
Supported Operating Systems: Platform Independent
Data Formats: Numpy
Tags: Classification, Regression, Gaussian Processes
Archive: download here

Other available revisons

Version Changelog Date
1.1

pyGPs v1.1 is released. It replaces pyGP_OO and contains substaintal updates in functionality and documentation. pyGP_PR v1.1 is released with substantial documentation updates and renamed (FN -> PR).

October 8, 2013, 12:35:28
1.0

Initial Announcement on mloss.org.

October 1, 2013, 14:12:14

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