step_range {recipes} | R Documentation |
step_range
creates a specification of a recipe step that will
normalize numeric data to have a standard deviation of one.
step_range(recipe, ..., role = NA, trained = FALSE, min = 0, max = 1, ranges = NULL)
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 will be
scaled. 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. |
min |
A single numeric value for the smallest value in the range |
max |
A single numeric value for the largest value in the range |
ranges |
A character vector of variables that will be normalized. Note
that this is ignored until the values are determined by
|
Scaling data means that the standard deviation of a variable is
divided out of the data. step_range
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) ranged_trans <- rec %>% step_range(carbon, hydrogen) ranged_obj <- prep(ranged_trans, training = biomass_tr) transformed_te <- bake(ranged_obj, biomass_te) biomass_te[1:10, names(transformed_te)] transformed_te