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 multiple processors for cross validation and subsampling is supported through
OpenMP. Development version is on github, please report package issues on
github.

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.

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.

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.

c(
person("Martin", "Vincent", role = "aut"),
person("Niels", "Richard Hansen", email = "niels.r.hansen@math.ku.dk", role = c("ctb", "cre"))
)
Martin Vincent [aut],
Niels Richard Hansen [ctb, cre]