| 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 | Deprecated fit function | 
| msgl.algorithm.config | Create a new algorithm configuration | 
| msgl.c.config | Featch information about the C side configuration of the... | 
| msgl.cv | Deprecated cv function | 
| msgl_dense_sgl_fit_R | C interface | 
| msgl_dense_sgl_lambda_R | C interface | 
| msgl_dense_sgl_predict_R | C interface | 
| msgl_dense_sgl_subsampling_R | C interface | 
| msgl.lambda.seq | Deprecated lambda function | 
| msgl-package | Multinomial logistic regression with sparse group lasso... | 
| msgl_sparse_sgl_fit_R | C interface | 
| msgl_sparse_sgl_lambda_R | C interface | 
| msgl_sparse_sgl_predict_R | C interface | 
| msgl_sparse_sgl_subsampling_R | C interface | 
| msgl.standard.config | Standard msgl algorithm configuration | 
| msgl.subsampling | Deprecated subsampling function | 
| 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 | 
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