User-Facing Functions

tune()

A placeholder function for argument values that are to be tuned.

tune_bayes()

Bayesian optimization of model parameters.

tune_grid()

Model tuning via grid search

fit_resamples()

Fit multiple models via resampling

last_fit()

Fit the final best model to the training set and evaluate the test set

prob_improve() exp_improve() conf_bound()

Acquisition function for scoring parameter combinations

control_bayes()

Control aspects of the Bayesian search process

control_grid() control_resamples()

Control aspects of the grid search process

autoplot(<tune_results>)

Plot tuning search results

coord_obs_pred()

Use same scale for plots of observed vs predicted values

expo_decay()

Exponential decay function

collect_predictions() collect_metrics()

Obtain and format results produced by tuning functions

filter_parameters()

Remove some tuning parameter results

show_best() select_best() select_by_pct_loss() select_by_one_std_err()

Investigate best tuning parameters

extract_recipe() extract_model()

Convenience functions to extract model or recipe

finalize_model() finalize_recipe() finalize_workflow()

Splice final parameters into objects

conf_mat_resampled()

Compute average confusion matrix across resamples

Low-Level Functions

merge(<recipe>) merge(<model_spec>)

Merge parameter grid values into objects

parameters(<workflow>) parameters(<model_spec>) parameters(<recipe>)

Determination of parameter sets for other objects

tunable() no_param

Find recommended methods for generating parameter values

tune_args()

Determine arguments tagged for tuning