juice {recipes} | R Documentation |
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.
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" 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). |
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.
recipe()
prep.recipe()
bake.recipe()
data(biomass) biomass_tr <- biomass[biomass$dataset == "Training",] biomass_te <- biomass[biomass$dataset == "Testing",] rec <- recipe(HHV ~ carbon + hydrogen + oxygen + nitrogen + sulfur, data = biomass_tr) sp_signed <- rec %>% step_center(all_predictors()) %>% step_scale(all_predictors()) %>% step_spatialsign(all_predictors()) sp_signed_trained <- prep(sp_signed, training = biomass_tr, retain = TRUE) tr_values <- bake(sp_signed_trained, newdata = biomass_tr, all_predictors()) og_values <- juice(sp_signed_trained, all_predictors()) all.equal(tr_values, og_values)