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Functions for tuning

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_last_fit()
Control aspects of the last fit process
autoplot(<tune_results>)
Plot tuning search results
augment(<tune_results>) augment(<resample_results>) augment(<last_fit>)
Augment data with holdout predictions
coord_obs_pred()
Use same scale for plots of observed vs predicted values
expo_decay()
Exponential decay function
collect_predictions() collect_metrics() collect_notes()
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
show_notes()
Display distinct errors from tune objects
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
extract_model()
Convenience functions to extract model
finalize_model() finalize_recipe() finalize_workflow()
Splice final parameters into objects
conf_mat_resampled()
Compute average confusion matrix across resamples
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
parameters(<workflow>) parameters(<model_spec>) parameters(<recipe>)
Determination of parameter sets for other 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
control_grid() control_resamples() new_backend_options()
Control aspects of the grid search process