Man pages for msgl
Multinomial Sparse Group Lasso
| 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 |
