Package index • tabnet

All functions
`autoplot.tabnet_explain()`	Plot tabnet_explain mask importance heatmap
`autoplot.tabnet_fit()` `autoplot.tabnet_pretrain()`	Plot tabnet_fit model loss along epochs
`check_compliant_node()`	Check that Node object names are compliant
`nn_prune_head.tabnet_fit()` `nn_prune_head.tabnet_pretrain()`	Prune top layer(s) of a tabnet network
`node_to_df()`	Turn a Node object into predictor and outcome.
`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
`cat_emb_dim()` `checkpoint_epochs()` `drop_last()` `encoder_activation()` `lr_scheduler()` `mlp_activation()` `mlp_hidden_multiplier()` `num_independent_decoder()` `num_shared_decoder()` `optimizer()` `penalty()` `verbose()` `virtual_batch_size()`	Non-tunable parameters for the tabnet model
`attention_width()` `decision_width()` `feature_reusage()` `momentum()` `mask_type()` `num_independent()` `num_shared()` `num_steps()`	Parameters for the tabnet model
`tabnet_pretrain()`	Tabnet model

Reference