msgl: High Dimensional Multiclass Classification Using Sparse Group Lasso
Version 2.3.6

Multinomial logistic regression with sparse group lasso penalty. Simultaneous feature selection and parameter estimation for classification. Suitable for high dimensional multiclass classification with many classes. The algorithm computes the sparse group lasso penalized maximum likelihood estimate. Use of parallel computing for cross validation and subsampling is supported through the 'foreach' and 'doParallel' packages. Development version is on GitHub, please report package issues on GitHub.

Package details

AuthorMartin Vincent
Date of publication2017-04-02 17:41:17 UTC
MaintainerMartin Vincent <[email protected]>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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msgl documentation built on May 29, 2017, 3:41 p.m.