# Tidy Tuning Tools

## Documentation for package ‘tune’ version 0.1.3

- DESCRIPTION file.

## Help Pages

ames_grid_search | Example Analysis of Ames Housing Data
ames_iter_search | Example Analysis of Ames Housing Data
ames_wflow | Example Analysis of Ames Housing Data
augment.last_fit | Augment data with holdout predictions
augment.resample_results | Augment data with holdout predictions
augment.tune_results | Augment data with holdout predictions
autoplot.tune_results | Plot tuning search results
collect_metrics | Obtain and format results produced by tuning functions
collect_metrics.tune_race | Obtain and format results produced by tuning functions
collect_metrics.tune_results | Obtain and format results produced by tuning functions
collect_predictions | Obtain and format results produced by tuning functions
collect_predictions.default | Obtain and format results produced by tuning functions
collect_predictions.tune_results | Obtain and format results produced by tuning functions
conf_bound | Acquisition function for scoring parameter combinations
conf_mat_resampled | Compute average confusion matrix across resamples
control_bayes | Control aspects of the Bayesian search process
control_grid | Control aspects of the grid search process
control_resamples | Control aspects of the grid search process
coord_obs_pred | Use same scale for plots of observed vs predicted values
example_ames_knn | Example Analysis of Ames Housing Data
expo_decay | Exponential decay function
exp_improve | Acquisition function for scoring parameter combinations
extract_model | Convenience functions to extract model or recipe
extract_recipe | Convenience functions to extract model or recipe
filter_parameters | Remove some tuning parameter results
finalize_model | Splice final parameters into objects
finalize_recipe | Splice final parameters into objects
finalize_workflow | Splice final parameters into objects
fit_resamples | Fit multiple models via resampling
fit_resamples.model_spec | Fit multiple models via resampling
fit_resamples.workflow | Fit multiple models via resampling
last_fit | Fit the final best model to the training set and evaluate the test set
last_fit.model_spec | Fit the final best model to the training set and evaluate the test set
last_fit.workflow | Fit the final best model to the training set and evaluate the test set
message_wrap | Write a message that respects the line width
prob_improve | Acquisition function for scoring parameter combinations
select_best | Investigate best tuning parameters
select_by_one_std_err | Investigate best tuning parameters
select_by_pct_loss | Investigate best tuning parameters
show_best | Investigate best tuning parameters
tune | A placeholder function for argument values that are to be tuned.
tune_bayes | Bayesian optimization of model parameters.
tune_bayes.model_spec | Bayesian optimization of model parameters.
tune_bayes.workflow | Bayesian optimization of model parameters.
tune_grid | Model tuning via grid search
tune_grid.model_spec | Model tuning via grid search
tune_grid.workflow | Model tuning via grid search