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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/range.R
\name{step_range}
\alias{step_range}
\alias{tidy.step_range}
\title{Scaling Numeric Data to a Specific Range}
\usage{
step_range(
recipe,
...,
role = NA,
trained = FALSE,
min = 0,
max = 1,
ranges = NULL,
skip = FALSE,
id = rand_id("range")
)
\method{tidy}{step_range}(x, ...)
}
\arguments{
\item{recipe}{A recipe object. The step will be added to the
sequence of operations for this recipe.}
\item{...}{One or more selector functions to choose which
variables will be scaled. See \code{\link[=selections]{selections()}} for more
details. For the \code{tidy} method, these are not currently
used.}
\item{role}{Not used by this step since no new variables are
created.}
\item{trained}{A logical to indicate if the quantities for
preprocessing have been estimated.}
\item{min}{A single numeric value for the smallest value in the
range.}
\item{max}{A single numeric value for the largest value in the
range.}
\item{ranges}{A character vector of variables that will be
normalized. Note that this is ignored until the values are
determined by \code{\link[=prep.recipe]{prep.recipe()}}. Setting this value will
be ineffective.}
\item{skip}{A logical. Should the step be skipped when the
recipe is baked by \code{\link[=bake.recipe]{bake.recipe()}}? While all operations are baked
when \code{\link[=prep.recipe]{prep.recipe()}} is run, some operations may not be able to be
conducted on new data (e.g. processing the outcome variable(s)).
Care should be taken when using \code{skip = TRUE} as it may affect
the computations for subsequent operations}
\item{id}{A character string that is unique to this step to identify it.}
\item{x}{A \code{step_range} object.}
}
\value{
An updated version of \code{recipe} with the new step
added to the sequence of existing steps (if any). For the
\code{tidy} method, a tibble with columns \code{terms} (the
selectors or variables selected), \code{min}, and \code{max}.
}
\description{
\code{step_range} creates a \emph{specification} of a recipe
step that will normalize numeric data to be within a pre-defined
range of values.
}
\details{
When a new data point is outside of the ranges seen in
the training set, the new values are truncated at \code{min} or
\code{max}.
}
\examples{
library(modeldata)
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)
}
\concept{normalization_methods}
\concept{preprocessing}
\keyword{datagen}
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