workflows (version 1.1.4)

add_recipe: Add a recipe to a workflow

Description

• add_recipe() specifies the terms of the model and any preprocessing that is required through the usage of a recipe.

• remove_recipe() removes the recipe as well as any downstream objects that might get created after the recipe is used for preprocessing, such as the prepped recipe. Additionally, if the model has already been fit, then the fit is removed.

• update_recipe() first removes the recipe, then replaces the previous recipe with the new one. Any model that has already been fit based on this recipe will need to be refit.

Usage

add_recipe(x, recipe, ..., blueprint = NULL)
remove_recipe(x)
update_recipe(x, recipe, ..., blueprint = NULL)

Value

x, updated with either a new or removed recipe preprocessor.

Arguments

x

A workflow

recipe

A recipe created using recipes::recipe(). The recipe should not have been trained already with recipes::prep(); workflows will handle training internally.

...

Not used.

blueprint

A hardhat blueprint used for fine tuning the preprocessing.

If NULL, hardhat::default_recipe_blueprint() is used.

Note that preprocessing done here is separate from preprocessing that might be done automatically by the underlying model.

Details

To fit a workflow, exactly one of add_formula(), add_recipe(), or add_variables() must be specified.

Examples

library(recipes)
library(magrittr)

recipe <- recipe(mpg ~ cyl, mtcars) %>%
  step_log(cyl)

workflow <- workflow() %>%
  add_recipe(recipe)

workflow

remove_recipe(workflow)

update_recipe(workflow, recipe(mpg ~ cyl, mtcars))