Package index
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autoplot.tabnet_explain()
- Plot tabnet_explain mask importance heatmap
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autoplot.tabnet_fit()
autoplot.tabnet_pretrain()
- Plot tabnet_fit model loss along epochs
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check_compliant_node()
- Check that Node object names are compliant
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entmax()
entmax15()
- Alpha-entmax
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get_tau()
- Optimal threshold (tau) computation for 1.5-entmax
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nn_aum_loss()
- AUM loss
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nn_prune_head(<tabnet_fit>)
nn_prune_head(<tabnet_pretrain>)
- Prune top layer(s) of a tabnet network
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node_to_df()
- Turn a Node object into predictor and outcome.
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sparsemax()
sparsemax15()
- Sparsemax
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tabnet()
- Parsnip compatible tabnet model
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tabnet_config()
- Configuration for TabNet models
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tabnet_explain()
- Interpretation metrics from a TabNet model
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tabnet_fit()
- Tabnet model
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tabnet_nn()
- TabNet Model Architecture
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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
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attention_width()
decision_width()
feature_reusage()
momentum()
mask_type()
num_independent()
num_shared()
num_steps()
- Parameters for the tabnet model
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tabnet_pretrain()
- Tabnet model