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step_range
creates a specification of a recipe
step that will normalize numeric data to be within a pre-defined
range of values.
step_range(recipe, ..., role = NA, trained = FALSE, min = 0, max = 1,
ranges = NULL)# S3 method for step_range
tidy(x, ...)
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 selections()
for more
details. For the tidy
method, these are not currently
used.
Not used by this step since no new variables are created.
A logical to indicate if the quantities for preprocessing have been estimated.
A single numeric value for the smallest value in the range
A single numeric value for the largest value in the range
A character vector of variables that will be
normalized. Note that this is ignored until the values are
determined by prep.recipe()
. Setting this value will
be ineffective.
A step_range
object.
An updated version of recipe
with the new step
added to the sequence of existing steps (if any). For the
tidy
method, a tibble with columns terms
(the
selectors or variables selected), min
, and max
.
When a new data point is outside of the ranges seen in
the training set, the new values are truncated at min
or
max
.
# NOT RUN {
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
tidy(ranged_trans, number = 1)
tidy(ranged_obj, number = 1)
# }
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