Extract Finalized Training Set
As of recipes version 0.1.14, juice() is superseded in favor of
bake(object, new_data = NULL).
juice(object, ..., composition = "tibble")
object |
A |
... |
One or more selector functions to choose which variables will be
returned by the function. See |
composition |
Either "tibble", "matrix", "data.frame", or "dgCMatrix" for the format of the processed data set. Note that all computations during the baking process are done in a non-sparse format. Also, note that this argument should be called after any selectors and the selectors should only resolve to numeric columns (otherwise an error is thrown). |
As steps are estimated by prep, these operations are
applied to the training set. Rather than running bake()
to duplicate this processing, this function will return
variables from the processed training set.
When preparing a recipe, if the training data set is
retained using retain = TRUE, there is no need to bake() the
recipe to get the preprocessed training set.
juice() will return the results of a recipe where all steps
have been applied to the data, irrespective of the value of
the step's skip argument.
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