step_textfeature {textrecipes} | R Documentation |
Calculate Set of Text Features
Description
step_textfeature()
creates a specification of a recipe step that will
extract a number of numeric features of a text column.
Usage
step_textfeature(
recipe,
...,
role = "predictor",
trained = FALSE,
columns = NULL,
extract_functions = count_functions,
prefix = "textfeature",
keep_original_cols = FALSE,
skip = FALSE,
id = rand_id("textfeature")
)
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 |
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 |
extract_functions |
A named list of feature extracting functions.
Defaults to |
prefix |
A prefix for generated column names, defaults to "textfeature". |
keep_original_cols |
A logical to keep the original variables in the
output. Defaults to |
skip |
A logical. Should the step be skipped when the
recipe is baked by |
id |
A character string that is unique to this step to identify it. |
Details
This step will take a character column and returns a number of numeric
columns equal to the number of functions in the list passed to the
extract_functions
argument.
All the functions passed to extract_functions
must take a character vector
as input and return a numeric vector of the same length, otherwise an error
will be thrown.
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 is returned with
columns terms
, functions
, and id
:
- terms
character, the selectors or variables selected
- functions
character, name of feature functions
- id
character, id of this step
Case weights
The underlying operation does not allow for case weights.
See Also
Other Steps for Numeric Variables From Characters:
step_dummy_hash()
,
step_sequence_onehot()
Examples
library(recipes)
library(modeldata)
data(tate_text)
tate_rec <- recipe(~., data = tate_text) %>%
step_textfeature(medium)
tate_obj <- tate_rec %>%
prep()
bake(tate_obj, new_data = NULL) %>%
slice(1:2)
bake(tate_obj, new_data = NULL) %>%
pull(textfeature_medium_n_words)
tidy(tate_rec, number = 1)
tidy(tate_obj, number = 1)
# Using custom extraction functions
nchar_round_10 <- function(x) round(nchar(x) / 10) * 10
recipe(~., data = tate_text) %>%
step_textfeature(medium,
extract_functions = list(nchar10 = nchar_round_10)
) %>%
prep() %>%
bake(new_data = NULL)