bake {recipes} | R Documentation |
For a recipe with at least one preprocessing operations that has been trained by
prep.recipe()
, apply the computations to new data.
bake(object, ...) ## S3 method for class 'recipe' bake(object, new_data = NULL, ..., composition = "tibble")
object |
A trained object such as a |
... |
One or more selector functions to choose which variables will be
returned by the function. See |
new_data |
A data frame or tibble for whom the preprocessing will be applied. |
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). |
bake()
takes a trained recipe and applies the
operations to a data set to create a design matrix.
If the original data used to train the data are to be
processed, time can be saved by using the retain = TRUE
option
of prep()
to avoid duplicating the same operations. With this
option set, juice()
can be used instead of bake
with
new_data
equal to the training set.
Also, any steps with skip = TRUE
will not be applied to the
data when bake
is invoked. juice()
will always have all
of the steps applied.
A tibble, matrix, or sparse matrix that may have different
columns than the original columns in new_data
.
Max Kuhn