Man pages for tabnet
Fit 'TabNet' Models for Classification and Regression
| autoplot.tabnet_explain | Plot tabnet_explain mask importance heatmap |
| autoplot.tabnet_fit | Plot tabnet_fit model loss along epochs |
| build_ancestor_matrix_from_outcomes | Build ancestor matrix aligned with observed outcome classes |
| check_compliant_node | Check that Node object names are compliant |
| entmax15 | Alpha-entmax |
| get_constr_output | Apply hierarchy constraints via max-pooling over descendants... |
| get_tau | Optimal threshold (tau) computation for 1.5-entmax |
| min_grid.tabnet | Determine the minimum set of model fits |
| nn_aum_loss | AUM loss |
| nnf_mc_loss | Max-Constraint Margin Loss (functional) |
| nnf_multilabel_one_hot | Convert class_id tensor to binary one-hot tensor |
| nn_mc_loss | Max-Constraint Margin Loss (module) |
| nn_prune_head | Prune top layer(s) of a tabnet network |
| node_to_df | Turn a Node object into predictor and outcome. |
| pipe | Pipe operator |
| predict.tabnet_fit | Predict using 'tabnet' |
| reexports | Objects exported from other packages |
| sparsemax | Sparsemax |
| tabnet | Parsnip compatible tabnet model |
| tabnet_config | Configuration for TabNet models |
| tabnet_explain | Interpretation metrics from a TabNet model |
| tabnet_fit | Tabnet model |
| tabnet_nn | TabNet Model Architecture |
| tabnet_non_tunable | Non-tunable parameters for the tabnet model |
| tabnet-package | tabnet: Fit 'TabNet' Models for Classification and Regression |
| tabnet_params | Parameters for the tabnet model |
| tabnet_pretrain | Tabnet model |
