textrecipes (version 1.1.0)

step_stopwords: Filtering of Stop Words for Tokens Variables

Description

step_stopwords() creates a specification of a recipe step that will filter a token variable for stop words.

Usage

step_stopwords(
  recipe,
  ...,
  role = NA,
  trained = FALSE,
  columns = NULL,
  language = "en",
  keep = FALSE,
  stopword_source = "snowball",
  custom_stopword_source = NULL,
  skip = FALSE,
  id = rand_id("stopwords")
)

Value

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

Arguments

recipe

A recipes::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

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 variable names that will be populated (eventually) by the terms argument. This is NULL until the step is trained by recipes::prep.recipe().

language

A character to indicate the language of stop words by ISO 639-1 coding scheme.

keep

A logical. Specifies whether to keep the stop words or discard them.

stopword_source

A character to indicate the stop words source as listed in stopwords::stopwords_getsources.

custom_stopword_source

A character vector to indicate a custom list of words that cater to the users specific problem.

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.

Tidying

When you tidy() this step, a tibble is returned with columns terms, value, keep, and id:

terms

character, the selectors or variables selected

value

character, name of stop word list

keep

logical, whether stop words are removed or kept

id

character, id of this step

Case weights

The underlying operation does not allow for case weights.

Details

Stop words are words which sometimes are removed before natural language processing tasks. While stop words usually refers to the most common words in the language there is no universal stop word list.

The argument custom_stopword_source allows you to pass a character vector to filter against. With the keep argument one can specify words to keep instead of removing thus allowing you to select words with a combination of these two arguments.

See Also

step_tokenize() to turn characters into tokens

Other Steps for Token Modification: step_lemma(), step_ngram(), step_pos_filter(), step_stem(), step_tokenfilter(), step_tokenmerge()

Examples

if (FALSE) { # rlang::is_installed(c("modeldata", "stopwords"))
library(recipes)
library(modeldata)
data(tate_text)
tate_rec <- recipe(~., data = tate_text) %>%
  step_tokenize(medium) %>%
  step_stopwords(medium)

tate_obj <- tate_rec %>%
  prep()

bake(tate_obj, new_data = NULL, medium) %>%
  slice(1:2)

bake(tate_obj, new_data = NULL) %>%
  slice(2) %>%
  pull(medium)

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

# With a custom stop words list

tate_rec <- recipe(~., data = tate_text) %>%
  step_tokenize(medium) %>%
  step_stopwords(medium, custom_stopword_source = c("twice", "upon"))
tate_obj <- tate_rec %>%
  prep(traimomg = tate_text)

bake(tate_obj, new_data = NULL) %>%
  slice(2) %>%
  pull(medium)
}