Function reference • hardhat

Preprocessing
`mold()`	Mold data for modeling
`forge()`	Forge prediction-ready data
Prediction
`spruce_numeric()` `spruce_class()` `spruce_prob()`	Spruce up predictions
Utility
`model_frame()`	Construct a model frame
`model_matrix()`	Construct a design matrix
`model_offset()`	Extract a model offset
`delete_response()`	Delete the response from a terms object
`standardize()`	Standardize the outcome
`new_model()`	Constructor for a base model
`add_intercept_column()`	Add an intercept column to `data`
`run_mold()`	Call `mold$clean()` and `mold$process()`
Validation
`scream()`	😱 Scream.
`shrink()`	Subset only required columns
`validate_column_names()` `check_column_names()`	Ensure that `data` contains required column names
`validate_no_formula_duplication()` `check_no_formula_duplication()`	Ensure no duplicate terms appear in `formula`
`validate_outcomes_are_binary()` `check_outcomes_are_binary()`	Ensure that the outcome has binary factors
`validate_outcomes_are_factors()` `check_outcomes_are_factors()`	Ensure that the outcome has only factor columns
`validate_outcomes_are_numeric()` `check_outcomes_are_numeric()`	Ensure outcomes are all numeric
`validate_outcomes_are_univariate()` `check_outcomes_are_univariate()`	Ensure that the outcome is univariate
`validate_prediction_size()` `check_prediction_size()`	Ensure that predictions have the correct number of rows
`validate_predictors_are_numeric()` `check_predictors_are_numeric()`	Ensure predictors are all numeric
Blueprint
`default_formula_blueprint()` `mold(<formula>)`	Default formula blueprint
`default_recipe_blueprint()` `mold(<recipe>)`	Default recipe blueprint
`default_xy_blueprint()` `mold(<data.frame>)` `mold(<matrix>)`	Default XY blueprint
`is_blueprint()`	Is `x` a preprocessing blueprint?
`new_formula_blueprint()` `new_recipe_blueprint()` `new_xy_blueprint()` `new_blueprint()`	Create a new preprocessing blueprint
`new_default_formula_blueprint()` `new_default_recipe_blueprint()` `new_default_xy_blueprint()`	Create a new default blueprint
`refresh_blueprint()`	Refresh a preprocessing blueprint
`update_blueprint()`	Update a preprocessing blueprint
Setup
`create_modeling_package()` `use_modeling_deps()` `use_modeling_files()`	Create a modeling package
Information
`get_data_classes()`	Extract data classes from a data frame or matrix
`get_levels()` `get_outcome_levels()`	Extract factor levels from a data frame
Data
`hardhat-example-data`	Example data for hardhat

Reference

Preprocessing

Prediction

Utility

Validation

Blueprint

Setup

Information

Data