Part of Speech Filtering of Token Variables

step_pos_filter() creates a specification of a recipe step that will filter a token variable based on part of speech tags.

Usage

step_pos_filter(
  recipe,
  ...,
  role = NA,
  trained = FALSE,
  columns = NULL,
  keep_tags = "NOUN",
  remove_tags = NULL,
  skip = FALSE,
  id = rand_id("pos_filter")
)

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 vector of the selected variable names. This is NULL until the step is trained by recipes::prep.recipe(), and should not be set by hand.
keep_tags: A character vector of part of speech tags to keep. See details for the complete list of tags. Defaults to "NOUN". Can't be used together with remove_tags.
remove_tags: A character vector of part of speech tags to remove, keeping all other tokens. See details for the complete list of tags. Defaults to NULL. Can't be used together with keep_tags.
skip: A logical. Should the step be skipped when the recipe is baked by recipes::bake()? While all operations are baked when recipes::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.

Value

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

Details

Possible part of speech tags for spacyr engine are: "ADJ", "ADP", "ADV", "AUX", "CONJ", "CCONJ", "DET", "INTJ", "NOUN", "NUM", "PART", "PRON", "PROPN", "PUNCT", "SCONJ", "SYM", "VERB", "X" and "SPACE". For more information look here https://github.com/explosion/spaCy/blob/master/spacy/glossary.py.

Tidying

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

terms: character, the selectors or variables selected
id: character, id of this step

Case weights

The underlying operation does not allow for case weights.

Examples

if (FALSE) { # \dontrun{
library(recipes)

short_data <- data.frame(text = c(
  "This is a short tale,",
  "With many cats and ladies."
))

rec_spec <- recipe(~text, data = short_data) |>
  step_tokenize(text, engine = "spacyr") |>
  step_pos_filter(text, keep_tags = "NOUN") |>
  step_tf(text)

rec_prepped <- prep(rec_spec)

bake(rec_prepped, new_data = NULL)
} # }