mold() applies the appropriate processing steps required to get training
data ready to be fed into a model. It does this through the use of various
blueprints that understand how to preprocess data that come in various
forms, such as a formula or a recipe.
All blueprints have consistent return values with the others, but each is
unique enough to have its own help page. Click through below to learn
how to use each one in conjunction with
XY Method -
Formula Method -
Recipes Method -
An object. See the method specific implementations linked in the Description for more information.
A named list containing 4 elements:
predictors: A tibble containing the molded predictors to be used in the
outcome: A tibble containing the molded outcomes to be used in the
blueprint: A method specific
"hardhat_blueprint" object for use when
NULL if the blueprint returns no extra information,
or a named list containing the extra information.
# See the method specific documentation linked in Description # for the details of each blueprint, and more examples. # XY mold(iris[, "Sepal.Width", drop = FALSE], iris$Species) # Formula mold(Species ~ Sepal.Width, iris) # Recipe library(recipes) mold(recipe(Species ~ Sepal.Width, iris), iris)
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