step_tokenmerge: Combine Multiple Token Variables Into One
In textrecipes: Extra 'Recipes' for Text Processing

step_tokenmerge

R Documentation

Combine Multiple Token Variables Into One

Description

step_tokenmerge() creates a specification of a recipe step that will take multiple token variables and combine them into one token variable.

Usage

step_tokenmerge(
  recipe,
  ...,
  role = "predictor",
  trained = FALSE,
  columns = NULL,
  prefix = "tokenmerge",
  keep_original_cols = FALSE,
  skip = FALSE,
  id = rand_id("tokenmerge")
)

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.
`role`	For model terms created by this step, what analysis role should they be assigned?. By default, the function assumes that the new columns created by the original variables will be used as predictors in a model.
`trained`	A logical to indicate if the quantities for preprocessing have been estimated.
`columns`	A character string of variable names that will be populated (eventually) by the `terms` argument. This is `NULL` until the step is trained by `recipes::prep.recipe()`.
`prefix`	A prefix for generated column names, default to "tokenmerge".
`keep_original_cols`	A logical to keep the original variables in the output. Defaults to `FALSE`.
`skip`	A logical. Should the step be skipped when the recipe is baked by `recipes::bake.recipe()`? While all operations are baked when `recipes::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 = FALSE`.
`id`	A character string that is unique to this step to identify it.

Value

An updated version of recipe with the new step added to the sequence of existing steps (if any).

Tidying

When you tidy() this step, a tibble with columns terms (the selectors or variables selected).

Case weights

The underlying operation does not allow for case weights.

Examples

library(recipes)
library(modeldata)
data(tate_text)

tate_rec <- recipe(~., data = tate_text) %>%
  step_tokenize(medium, artist) %>%
  step_tokenmerge(medium, artist)

tate_obj <- tate_rec %>%
  prep()

bake(tate_obj, new_data = NULL)

tidy(tate_rec, number = 2)
tidy(tate_obj, number = 2)

textrecipes documentation built on Nov. 16, 2023, 5:06 p.m.