Fit 'TabNet' Models for Classification and Regression
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Documentation for package ‘tabnet’ version 0.9.0
Help Pages
| attention_width | Parameters for the tabnet model |
| augment.tabnet_fit | Predict using 'tabnet' |
| autoplot.tabnet_explain | Plot tabnet_explain mask importance heatmap |
| autoplot.tabnet_fit | Plot tabnet_fit model loss along epochs |
| autoplot.tabnet_pretrain | Plot tabnet_fit model loss along epochs |
| build_ancestor_matrix_from_outcomes | Build ancestor matrix aligned with observed outcome classes |
| cat_emb_dim | Non-tunable parameters for the tabnet model |
| checkpoint_epochs | Non-tunable parameters for the tabnet model |
| check_compliant_node | Check that Node object names are compliant |
| decision_width | Parameters for the tabnet model |
| drop_last | Non-tunable parameters for the tabnet model |
| encoder_activation | Non-tunable parameters for the tabnet model |
| entmax | Alpha-entmax |
| entmax15 | Alpha-entmax |
| feature_reusage | Parameters for the tabnet model |
| get_constr_output | Apply hierarchy constraints via max-pooling over descendants (MCM) |
| get_tau | Optimal threshold (tau) computation for 1.5-entmax |
| lr_scheduler | Non-tunable parameters for the tabnet model |
| mask_type | Parameters for the tabnet model |
| mlp_activation | Non-tunable parameters for the tabnet model |
| mlp_hidden_multiplier | Non-tunable parameters for the tabnet model |
| momentum | Parameters for the tabnet model |
| nnf_mc_loss | Max-Constraint Margin Loss (functional) |
| nnf_multilabel_one_hot | Convert class_id tensor to binary one-hot tensor |
| nn_aum_loss | AUM loss |
| nn_mc_loss | Max-Constraint Margin Loss (module) |
| nn_prune_head.tabnet_fit | Prune top layer(s) of a tabnet network |
| nn_prune_head.tabnet_pretrain | Prune top layer(s) of a tabnet network |
| node_to_df | Turn a Node object into predictor and outcome. |
| num_independent | Parameters for the tabnet model |
| num_independent_decoder | Non-tunable parameters for the tabnet model |
| num_shared | Parameters for the tabnet model |
| num_shared_decoder | Non-tunable parameters for the tabnet model |
| num_steps | Parameters for the tabnet model |
| optimizer | Non-tunable parameters for the tabnet model |
| penalty | Non-tunable parameters for the tabnet model |
| predict.tabnet_fit | Predict using 'tabnet' |
| sparsemax | Sparsemax |
| sparsemax15 | Sparsemax |
| tabnet | Parsnip compatible tabnet model |
| tabnet_config | Configuration for TabNet models |
| tabnet_explain | Interpretation metrics from a TabNet model |
| tabnet_explain.default | Interpretation metrics from a TabNet model |
| tabnet_explain.model_fit | Interpretation metrics from a TabNet model |
| tabnet_explain.tabnet_fit | Interpretation metrics from a TabNet model |
| tabnet_explain.tabnet_pretrain | Interpretation metrics from a TabNet model |
| tabnet_fit | Tabnet model |
| tabnet_fit.data.frame | Tabnet model |
| tabnet_fit.default | Tabnet model |
| tabnet_fit.formula | Tabnet model |
| tabnet_fit.Node | Tabnet model |
| tabnet_fit.recipe | Tabnet model |
| tabnet_nn | TabNet Model Architecture |
| tabnet_pretrain | Tabnet model |
| tabnet_pretrain.data.frame | Tabnet model |
| tabnet_pretrain.default | Tabnet model |
| tabnet_pretrain.formula | Tabnet model |
| tabnet_pretrain.Node | Tabnet model |
| tabnet_pretrain.recipe | Tabnet model |
| verbose | Non-tunable parameters for the tabnet model |
| virtual_batch_size | Non-tunable parameters for the tabnet model |