# High Dimensional Multiclass Classification Using Sparse Group Lasso

## Documentation for package ‘msgl’ version 2.3.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

best_model.msgl | Index of best model
coef.msgl | Extract nonzero coefficients
Err.msgl | Compute error rates
features.msgl | Nonzero features
features_stat.msgl | Extract feature statistics
models.msgl | Extract the fitted models
msgl | Fit a multinomial sparse group lasso regularization path.
msgl.algorithm.config | Create a new algorithm configuration
msgl.cv | Multinomial sparse group lasso cross validation
msgl.lambda.seq | Computes a lambda sequence for the regularization path
msgl.standard.config | Standard msgl algorithm configuration
msgl.subsampling | Multinomial sparse group lasso generic subsampling procedure
nmod.msgl | Returns the number of models in a msgl object
parameters.msgl | Nonzero parameters
parameters_stat.msgl | Extracting parameter statistics
predict.msgl | Predict
print.msgl | Print function for msgl
sim.data | Simulated data set