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glm-ie: The Generalised Linear Models Inference and Estimation Toolbox
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 The code is fully compatible to both Matlab 7.x and GNU Octave 3.3.x. Abstract Probabilistic classification, sparse linear modelling and logistic regression are covered in a common algorithmical framework.
@article{6939, title = {glm-ie: The Generalised Linear Models Inference and Estimation Toolbox}, journal = {Journal of Machine Learning Research}, abstract = {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 The code is fully compatible to both Matlab 7.x and GNU Octave 3.3.x. Abstract Probabilistic classification, sparse linear modelling and logistic regression are covered in a common algorithmical framework.}, volume = {13}, pages = {1699-1703}, organization = {Max-Planck-Gesellschaft}, school = {Biologische Kybernetik}, month = may, year = {2012}, slug = {6939}, author = {Nickisch, H.}, month_numeric = {5} }