High dimensional multiclass classification using sparse group lasso

Documentation for package ‘msgl’ version 2.0.125.0

coef.msgl	Extract nonzero coefficients
Err.msgl	Compute error rates
features.msgl	Nonzero features
models.msgl	Exstract 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
predict.msgl	Predict
print.msgl	Print function for msgl
sim.data	Simulated data set