step_robust: Perform Robust Scaling

In extrasteps: More Miscellaneous Steps for the 'recipes' Package

Perform Robust Scaling

Description

step_robust() creates a specification of a recipe step that will perform Robust scaling.

Usage

step_robust(
  recipe,
  ...,
  role = NA,
  trained = FALSE,
  range = c(0.25, 0.75),
  res = NULL,
  columns = NULL,
  skip = FALSE,
  id = rand_id("robust")
)

Arguments

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 recipes::selections() for more details. For the tidy method, these are not currently used.
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.
range	A numeric vector with 2 values denoting the lower and upper quantile that is used for scaling. Defaults to c(0.25, 0.75).
res	A list containing the 3 quantiles of training variables is stored here once this preprocessing step has be trained by recipes::prep().
columns	A character string of variable names that will be populated (eventually) by the terms argument.
skip	A logical. Should the step be skipped when the recipe is baked by bake()? While all operations are baked when prep() 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 skip = TRUE as it may affect the computations for subsequent operations.
id	A character string that is unique to this step to identify it.

Details

The scaling performed by this step is done using the following transformation

x_new = (x - Q2(x)) / (Q3(x) - Q1(x))

where Q2(x) is the median, Q3(x) is the upper quantile (defaults to 0.75) and Q1(x) is the lower quantile (defaults to 0.25). The upper and lower quantiles can be changed with the range argument.

Value

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 columns that will be affected) and base.

Examples

library(recipes)

rec <- recipe(~., data = mtcars) %>%
  step_robust(all_predictors()) %>%
  prep()

rec %>%
  bake(new_data = NULL)

tidy(rec, 1)

rec <- recipe(~., data = mtcars) %>%
  step_robust(all_predictors(), range = c(0.1, 0.9)) %>%
  prep()

rec %>%
  bake(new_data = NULL)

tidy(rec, 1)

extrasteps documentation built on Oct. 4, 2024, 1:07 a.m.