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.
| Version: | 2.3.6 |
| Depends: | R (≥ 3.2.4), Matrix, sglOptim (== 1.3.6) |
| Imports: | methods, tools, utils, stats |
| LinkingTo: | Rcpp, RcppProgress, RcppArmadillo, BH, sglOptim |
| Suggests: | knitr, rmarkdown |
| Published: | 2017-04-02 |
| Author: | Martin Vincent |
| Maintainer: | Martin Vincent <martin.vincent.dk at gmail.com> |
| BugReports: | https://github.com/vincent-dk/msgl/issues |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | http://www.sciencedirect.com/science/article/pii/S0167947313002168, https://github.com/vincent-dk/msgl |
| NeedsCompilation: | yes |
| Citation: | msgl citation info |
| Materials: | NEWS |
| CRAN checks: | msgl results |
| Reference manual: | msgl.pdf |
| Vignettes: |
Quick Start Quick Start |
| Package source: | msgl_2.3.6.tar.gz |
| Windows binaries: | r-devel: msgl_2.3.6.zip, r-release: msgl_2.3.6.zip, r-oldrel: msgl_2.3.6.zip |
| OS X El Capitan binaries: | r-release: msgl_2.3.6.tgz |
| OS X Mavericks binaries: | r-oldrel: msgl_2.3.6.tgz |
| Old sources: | msgl archive |
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