recipes: step_ordinalscore – R documentation

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step_ordinalscore

Convert Ordinal Factors to Numeric Scores

Description

step_ordinalscore creates a specification of a recipe step that will convert ordinal factor variables into numeric scores.

Usage

step_ordinalscore(
  recipe,
  ...,
  role = NA,
  trained = FALSE,
  columns = NULL,
  convert = as.numeric,
  skip = FALSE,
  id = rand_id("ordinalscore")
)

## S3 method for class 'step_ordinalscore'
tidy(x, ...)

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 `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.
`columns`	A character string of variables that will be converted. This is `NULL` until computed by `prep.recipe()`.
`convert`	A function that takes an ordinal factor vector as an input and outputs a single numeric variable.
`skip`	A logical. Should the step be skipped when the recipe is baked by `bake.recipe()`? While all operations are baked when `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 `skip = TRUE` as it may affect the computations for subsequent operations
`id`	A character string that is unique to this step to identify it.
`x`	A `step_ordinalscore` object.

Details

Dummy variables from ordered factors with C levels will create polynomial basis functions with C-1 terms. As an alternative, this step can be used to translate the ordered levels into a single numeric vector of values that represent (subjective) scores. By default, the translation uses a linear scale (1, 2, 3, ... C) but custom score functions can also be used (see the example below).

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).

Examples

fail_lvls <- c("meh", "annoying", "really_bad")

ord_data <-
  data.frame(item = c("paperclip", "twitter", "airbag"),
             fail_severity = factor(fail_lvls,
                                    levels = fail_lvls,
                                    ordered = TRUE))

model.matrix(~fail_severity, data = ord_data)

linear_values <- recipe(~ item + fail_severity, data = ord_data) %>%
  step_dummy(item) %>%
  step_ordinalscore(fail_severity)

linear_values <- prep(linear_values, training = ord_data)

bake(linear_values, new_data = NULL, everything())

custom <- function(x) {
  new_values <- c(1, 3, 7)
  new_values[as.numeric(x)]
}

nonlin_scores <- recipe(~ item + fail_severity, data = ord_data) %>%
  step_dummy(item) %>%
  step_ordinalscore(fail_severity, convert = custom)

tidy(nonlin_scores, number = 2)

nonlin_scores <- prep(nonlin_scores, training = ord_data)

bake(nonlin_scores, new_data = NULL, everything())

tidy(nonlin_scores, number = 2)

recipes

Preprocessing Tools to Create Design Matrices

v0.1.16

MIT + file LICENSE

Authors

Max Kuhn [aut, cre], Hadley Wickham [aut], RStudio [cph]

Initial release