Obtain and format results produced by tuning functions
Compute average confusion matrix across resamples
Control aspects of the Bayesian search process
Control aspects of the grid search process
Use same scale for plots of observed vs predicted values
Determine if case weights should be passed on to yardstick
Fit a model to the numerically optimal configuration
Fit the final best model to the training set and evaluate the test set
Merge parameter grid values into objects
Write a message that respects the line width
Determine names of the outcome data in a workflow
Determination of parameter sets for other objects
Acquisition function for scoring parameter combinations
Display distinct errors from tune objects
Internal functions used by other tidymodels packages
Bayesian optimization of model parameters.