step_stopwords: Filtering of stopwords from a list-column variable

Description Usage Arguments Details Value See Also Examples

Description

'step_stopwords' creates a *specification* of a recipe step that will filter a list of tokens for stopwords(keep or remove).

Usage

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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"))

## S3 method for class 'step_stopwords'
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 variables. For 'step_stopwords', this indicates the variables to be encoded into a list column. 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 recipe has been baked.

columns

A list of tibble results that define the encoding. This is 'NULL' until the step is trained by [recipes::prep.recipe()].

language

A character to indicate the langauge of stopwords by ISO 639-1 coding scheme.

keep

A logical. Specifies whether to keep the stopwords or discard them.

stopword_source

A character to indicate the stopwords 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 = 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_stopwords' object.

Details

Stop words are words which sometimes are remove before natural language processing tasks. While stop words usually refers to the most common words in the laguange 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 to keep the words instead of removing thus allowing you to select words with a combination of these two arguments.

Value

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

See Also

[step_stem()] [step_tokenfilter()] [step_tokenize()]

Examples

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library(recipes)

data(okc_text)

okc_rec <- recipe(~ ., data = okc_text) %>%
  step_tokenize(essay0) %>%
  step_stopwords(essay0) 
  
okc_obj <- okc_rec %>%
  prep(training = okc_text, retain = TRUE)

juice(okc_obj, essay0) %>% 
  slice(1:2)

juice(okc_obj) %>% 
  slice(2) %>% 
  pull(essay0) 
  
tidy(okc_rec, number = 2)
tidy(okc_obj, number = 2)
# With a custom stopwords list

okc_rec <- recipe(~ ., data = okc_text) %>%
  step_tokenize(essay0) %>%
  step_stopwords(essay0, custom_stopword_source = c("twice", "upon"))
okc_obj <- okc_rec %>%
  prep(traimomg = okc_text, retain = TRUE)
  
juice(okc_obj) %>%
  slice(2) %>%
  pull(essay0) 

textrecipes documentation built on May 2, 2019, 1:27 p.m.