Package: msgl
Type: Package
Title: High Dimensional Multiclass Classification Using Sparse Group
        Lasso
Version: 2.2.0
Date: 2015-09-16
Author: Martin Vincent
Maintainer: Martin Vincent <vincent@math.ku.dk>
Description: Multinomial logistic regression with sparse group lasso penalty. Suitable for high dimensional multiclass classification with many classes. The algorithm finds the sparse group lasso penalized maximum likelihood estimator. This result in feature and parameter selection, and parameter estimation. Use of multiple processors for cross validation and subsampling is supported through OpenMP. Development version is on github.
URL: http://dx.doi.org/10.1016/j.csda.2013.06.004
        https://github.com/vincent-dk/msgl
License: GPL (>= 2)
LazyLoad: yes
Imports: methods, utils, stats
Depends: R (>= 3.0.0), Matrix, sglOptim (== 1.2.0)
LinkingTo: Rcpp, RcppProgress, RcppArmadillo, BH, sglOptim
NeedsCompilation: yes
Packaged: 2015-09-19 20:43:34 UTC; martin
Repository: CRAN
Date/Publication: 2015-09-19 22:46:48
