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Documentation for package ‘hardhat’ version 1.3.0

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modeling-package Create a modeling package
add_intercept_column Add an intercept column to 'data'
check_column_names Ensure that 'data' contains required column names
check_no_formula_duplication Ensure no duplicate terms appear in 'formula'
check_outcomes_are_binary Ensure that the outcome has binary factors
check_outcomes_are_factors Ensure that the outcome has only factor columns
check_outcomes_are_numeric Ensure outcomes are all numeric
check_outcomes_are_univariate Ensure that the outcome is univariate
check_prediction_size Ensure that predictions have the correct number of rows
check_predictors_are_numeric Ensure predictors are all numeric
create_modeling_package Create a modeling package
default_formula_blueprint Default formula blueprint
default_recipe_blueprint Default recipe blueprint
default_xy_blueprint Default XY blueprint
delete_response Delete the response from a terms object
example_test Example data for hardhat
example_train Example data for hardhat
extract_fit_engine Generics for object extraction
extract_fit_parsnip Generics for object extraction
extract_mold Generics for object extraction
extract_parameter_dials Generics for object extraction
extract_parameter_set_dials Generics for object extraction
extract_preprocessor Generics for object extraction
extract_recipe Generics for object extraction
extract_spec_parsnip Generics for object extraction
extract_workflow Generics for object extraction
fct_encode_one_hot Encode a factor as a one-hot indicator matrix
forge Forge prediction-ready data
frequency_weights Frequency weights
get_data_classes Extract data classes from a data frame or matrix
get_levels Extract factor levels from a data frame
get_outcome_levels Extract factor levels from a data frame
hardhat-example-data Example data for hardhat
hardhat-extract Generics for object extraction
importance_weights Importance weights
is_blueprint Is 'x' a preprocessing blueprint?
is_case_weights Is 'x' a case weights vector?
is_frequency_weights Is 'x' a frequency weights vector?
is_importance_weights Is 'x' an importance weights vector?
model_frame Construct a model frame
model_matrix Construct a design matrix
model_offset Extract a model offset
mold Mold data for modeling
mold.data.frame Default XY blueprint
mold.formula Default formula blueprint
mold.matrix Default XY blueprint
mold.recipe Default recipe blueprint
new-blueprint Create a new preprocessing blueprint
new-default-blueprint Create a new default blueprint
new_blueprint Create a new preprocessing blueprint
new_case_weights Extend case weights
new_default_formula_blueprint Create a new default blueprint
new_default_recipe_blueprint Create a new default blueprint
new_default_xy_blueprint Create a new default blueprint
new_formula_blueprint Create a new preprocessing blueprint
new_frequency_weights Construct a frequency weights vector
new_importance_weights Construct an importance weights vector
new_model Constructor for a base model
new_recipe_blueprint Create a new preprocessing blueprint
new_xy_blueprint Create a new preprocessing blueprint
refresh_blueprint Refresh a preprocessing blueprint
run-forge 'forge()' according to a blueprint
run-mold 'mold()' according to a blueprint
run_forge 'forge()' according to a blueprint
run_forge.default_formula_blueprint 'forge()' according to a blueprint
run_forge.default_recipe_blueprint 'forge()' according to a blueprint
run_forge.default_xy_blueprint 'forge()' according to a blueprint
run_mold 'mold()' according to a blueprint
run_mold.default_formula_blueprint 'mold()' according to a blueprint
run_mold.default_recipe_blueprint 'mold()' according to a blueprint
run_mold.default_xy_blueprint 'mold()' according to a blueprint
scream Scream.
shrink Subset only required columns
spruce Spruce up predictions
spruce-multiple Spruce up multi-outcome predictions
spruce_class Spruce up predictions
spruce_class_multiple Spruce up multi-outcome predictions
spruce_numeric Spruce up predictions
spruce_numeric_multiple Spruce up multi-outcome predictions
spruce_prob Spruce up predictions
spruce_prob_multiple Spruce up multi-outcome predictions
standardize Standardize the outcome
tune Mark arguments for tuning
update_blueprint Update a preprocessing blueprint
use_modeling_deps Create a modeling package
use_modeling_files Create a modeling package
validate_column_names Ensure that 'data' contains required column names
validate_no_formula_duplication Ensure no duplicate terms appear in 'formula'
validate_outcomes_are_binary Ensure that the outcome has binary factors
validate_outcomes_are_factors Ensure that the outcome has only factor columns
validate_outcomes_are_numeric Ensure outcomes are all numeric
validate_outcomes_are_univariate Ensure that the outcome is univariate
validate_prediction_size Ensure that predictions have the correct number of rows
validate_predictors_are_numeric Ensure predictors are all numeric
weighted_table Weighted table