High Dimensional Multiclass Classification Using Sparse Group Lasso

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Documentation for package ‘msgl’ version 2.0.125.1

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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