Man pages for ipapercodes/FGSPCA
Feature Grouping and Sparse Principal Component Analysis (FGSPCA)
| convcheck | Convergence check of two successive matrices |
| coordinate_descent_enet | The coordinate descent for the standard elastic net... |
| coordinate_descent_LASSO | The coordinate descent for LASSO (elastic net) regression |
| different_beta_solver | Different beta solvers |
| enet_loss | The elastic net loss function |
| FGSPCA | Feature Grouping and Sparse PCA with L2 loss function. |
| FSGFunL2 | The Feature Selection and Grouping Function FSGFun with L2... |
| ObjFun_FG_S_PCA_L2 | Objective Function of Feature Grouping and Sparse PCA with L2... |
| ObjFunL2 | The objective function using L2 loss with three penalty... |
| PenaltyFun | The penalty function consisting of three parts. |
| rootmatrix | Calculate the root matrix of the given square matrix using... |
| solvebeta | The SPCA solver of beta for the elastic net problem |
| total_variance_explained | Adjusted Total Variance by Zou. et.al.(2006) |
