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

extract_resample_weights(): Extract resample weights from rset or tuning 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

add_resample_weights(): Add resample weights to an rset object

calculate_resample_weights(): Calculate resample weights from resample sizes

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