Fit 'TabNet' Models for Classification and Regression


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Documentation for package ‘tabnet’ version 0.6.0

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attention_width Parameters for the tabnet model
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
check_compliant_node Check that Node object names are compliant
decision_width Parameters for the tabnet model
feature_reusage Parameters for the tabnet model
mask_type Parameters for the tabnet model
momentum Parameters for the tabnet model
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_shared Parameters for the tabnet model
num_steps Parameters for the tabnet model
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