Package index • tune

Fit many models
`tune_grid()`	Model tuning via grid search
`tune_bayes()`	Bayesian optimization of model parameters.
`expo_decay()`	Exponential decay function
`prob_improve()` `exp_improve()` `conf_bound()`	Acquisition function for scoring parameter combinations
`fit_resamples()`	Fit multiple models via resampling
`control_grid()` `control_resamples()` `new_backend_options()`	Control aspects of the grid search process
`control_bayes()`	Control aspects of the Bayesian search process
`parallelism`	Support for parallel processing in tune
Fit one model
`fit_best()`	Fit a model to the numerically optimal configuration
`last_fit()`	Fit the final best model to the training set and evaluate the test set
`finalize_model()` `finalize_recipe()` `finalize_workflow()` `finalize_tailor()`	Splice final parameters into objects
`control_last_fit()`	Control aspects of the last fit process
Inspect results
`collect_predictions()` `collect_metrics()` `collect_notes()` `collect_extracts()`	Obtain and format results produced by tuning functions
`show_notes()`	Display distinct errors from tune objects
`show_best()` `select_best()` `select_by_pct_loss()` `select_by_one_std_err()`	Investigate best tuning parameters
`filter_parameters()`	Remove some tuning parameter results
`autoplot(<tune_results>)`	Plot tuning search results
`coord_obs_pred()`	Use same scale for plots of observed vs predicted values
`conf_mat_resampled()`	Compute average confusion matrix across resamples
Miscellaneous
`extract_workflow(<last_fit>)` `extract_workflow(<tune_results>)` `extract_spec_parsnip(<tune_results>)` `extract_recipe(<tune_results>)` `extract_fit_parsnip(<tune_results>)` `extract_fit_engine(<tune_results>)` `extract_mold(<tune_results>)` `extract_preprocessor(<tune_results>)`	Extract elements of `tune` objects
`int_pctl(<tune_results>)`	Bootstrap confidence intervals for performance metrics
`compute_metrics()`	Calculate and format metrics from tuning functions
`augment(<tune_results>)` `augment(<resample_results>)` `augment(<last_fit>)`	Augment data with holdout predictions
`example_ames_knn` `ames_wflow` `ames_grid_search` `ames_iter_search`	Example Analysis of Ames Housing Data
Developer functions
`merge(<recipe>)` `merge(<model_spec>)`	Merge parameter grid values into objects
`message_wrap()`	Write a message that respects the line width
`.use_case_weights_with_yardstick()`	Determine if case weights should be passed on to yardstick
`.stash_last_result()`	Save most recent results to search path

Reference

Fit many models

Fit one model

Inspect results

Miscellaneous

Developer functions