step_scale {recipes} | R Documentation |
step_scale
creates a specification of a recipe step that
will normalize numeric data to have a standard deviation of one.
step_scale(recipe, ..., role = NA, trained = FALSE, sds = NULL, na.rm = TRUE)
recipe |
A recipe object. The step will be added to the sequence of operations for this recipe. |
... |
One or more selector functions to choose which variables are
affected by the step. See |
role |
Not used by this step since no new variables are created. |
trained |
A logical to indicate if the quantities for preprocessing have been estimated. |
sds |
A named numeric vector of standard deviations This is |
na.rm |
A logical value indicating whether |
Scaling data means that the standard deviation of a variable is
divided out of the data. step_scale
estimates the variable
standard deviations from the data used in the training
argument of
prep.recipe
. bake.recipe
then applies the scaling to
new data sets using these standard deviations.
An updated version of recipe
with the
new step added to the sequence of existing steps (if any).
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) scaled_trans <- rec %>% step_scale(carbon, hydrogen) scaled_obj <- prep(scaled_trans, training = biomass_tr) transformed_te <- bake(scaled_obj, biomass_te) biomass_te[1:10, names(transformed_te)] transformed_te