Multinomial Sparse Group Lasso


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Documentation for package ‘msgl’ version 2.3.9

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msgl-package Multinomial logistic regression with sparse group lasso penalty.
best_model.msgl Index of best model
classes Class vector
coef.msgl Nonzero coefficients
cv Cross Validation
Err.msgl Compute error rates
features.msgl Nonzero features
features_stat.msgl Extract feature statistics
fit Fit a multinomial sparse group lasso regularization path.
lambda Computes a lambda sequence for the regularization path
models.msgl Extract the fitted models
msgl.algorithm.config Create a new algorithm configuration
msgl.c.config Featch information about the C side configuration of the package
msgl.standard.config Standard msgl algorithm configuration
nmod.msgl Number of models used for fitting
parameters.msgl Nonzero parameters
parameters_stat.msgl Extracting parameter statistics
predict.msgl Predict
PrimaryCancers Primary cancer samples.
print.msgl Print function for msgl
SimData Simulated data set
subsampling Multinomial sparse group lasso generic subsampling procedure
x Design matrix