Project details for The Generalised Linear Models Inference and Estimation Toolbox

Logo JMLR The Generalised Linear Models Inference and Estimation Toolbox 1.5

by hn - November 8, 2013, 13:58:03 CET [ Project Homepage BibTeX Download ]

view ( today), download ( today ), 0 subscriptions


The glm-ie toolbox contains scalable estimation routines for GLMs (generalised linear models) and SLMs (sparse linear models) as well as an implementation of a scalable convex variational Bayesian inference relaxation. We designed the glm-ie package to be simple, generic and easily expansible. Most of the code is written in Matlab including some MEX files. The code is fully compatible to both Matlab 7.x and GNU Octave 3.2.x.

Probabilistic classification, sparse linear modelling and logistic regression are covered in a common algorithmical framework allowing for both MAP estimation and approximate Bayesian inference.

Changes to previous version:

added factorial mean field inference as a third algorithm complementing expectation propagation and variational Bayes

generalised non-Gaussian potentials so that affine instead of linear functions of the latent variables can be used

BibTeX Entry: Download
Supported Operating Systems: Agnostic, Platform Independent
Data Formats: Matlab, Octave
Tags: Approximate Inference, Sparse Learning, Logistic Regression
Archive: download here


No one has posted any comments yet. Perhaps you'd like to be the first?

Leave a comment

You must be logged in to post comments.