Tidy Tuning Tools

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Documentation for package ‘tune’ version 1.1.1

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.stash_last_result Save most recent results to search path
.use_case_weights_with_yardstick Determine if case weights should be passed on to yardstick
.use_case_weights_with_yardstick.hardhat_frequency_weights Determine if case weights should be passed on to yardstick
.use_case_weights_with_yardstick.hardhat_importance_weights Determine if case weights should be passed on to yardstick
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_extracts Obtain and format results produced by tuning functions
collect_extracts.tune_results Obtain and format results produced by tuning functions
collect_metrics Obtain and format results produced by tuning functions
collect_metrics.tune_results Obtain and format results produced by tuning functions
collect_notes Obtain and format results produced by tuning functions
collect_notes.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_last_fit Control aspects of the last fit 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-tune Extract elements of 'tune' objects
extract_fit_engine.tune_results Extract elements of 'tune' objects
extract_fit_parsnip.tune_results Extract elements of 'tune' objects
extract_model Convenience functions to extract model
extract_mold.tune_results Extract elements of 'tune' objects
extract_preprocessor.tune_results Extract elements of 'tune' objects
extract_recipe.tune_results Extract elements of 'tune' objects
extract_spec_parsnip.tune_results Extract elements of 'tune' objects
extract_workflow.last_fit Extract elements of 'tune' objects
extract_workflow.tune_results Extract elements of 'tune' objects
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_best Fit a model to the numerically optimal configuration
fit_best.default Fit a model to the numerically optimal configuration
fit_best.tune_results Fit a model to the numerically optimal configuration
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_best.default Investigate best tuning parameters
select_best.tune_results Investigate best tuning parameters
select_by_one_std_err Investigate best tuning parameters
select_by_one_std_err.default Investigate best tuning parameters
select_by_one_std_err.tune_results Investigate best tuning parameters
select_by_pct_loss Investigate best tuning parameters
select_by_pct_loss.default Investigate best tuning parameters
select_by_pct_loss.tune_results Investigate best tuning parameters
show_best Investigate best tuning parameters
show_best.default Investigate best tuning parameters
show_best.tune_results Investigate best tuning parameters
show_notes Display distinct errors from tune objects
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