Creating Modeling Packages with hardhat

The hardhat package provides infrastructure for building modeling packages with consistent interfaces. It standardizes preprocessing via mold() (training) and forge() (prediction), handling formula, XY, and recipe inputs uniformly.

Quick Reference

Task	Function
Preprocess training data	`mold(x, y)` or `mold(formula, data)`
Preprocess prediction data	`forge(new_data, blueprint)`
Create model object	`new_model(..., blueprint, class)`
XY blueprint	`default_xy_blueprint(intercept = TRUE)`
Formula blueprint	`default_formula_blueprint(intercept = TRUE)`
Recipe blueprint	`default_recipe_blueprint(intercept = TRUE)`
Format numeric predictions	`spruce_numeric(pred)`
Format class predictions	`spruce_class(pred)`
Format probability predictions	`spruce_prob(pred)`
Validate univariate outcome	`validate_outcomes_are_univariate(outcomes)`
Validate prediction size	`validate_prediction_size(pred, new_data)`