step_bin2factor creates a specification of a
recipe step that will create a two-level factor from a single
step_bin2factor( recipe, ..., role = NA, trained = FALSE, levels = c("yes", "no"), ref_first = TRUE, columns = NULL, skip = FALSE, id = rand_id("bin2factor") ) # S3 method for step_bin2factor tidy(x, ...)
A recipe object. The step will be added to the sequence of operations for this recipe.
Selector functions that choose which variables will
be converted. See
Not used by this step since no new variables are created.
A logical to indicate if the quantities for preprocessing have been estimated.
A length 2 character string that indicates the factor levels for the 1's (in the first position) and the zeros (second)
Logical. Should the first level, which replaces 1's, be the factor reference level?
A vector with the selected variable names. This
A logical. Should the step be skipped when the
recipe is baked by
A character string that is unique to this step to identify it.
An updated version of
recipe with the new step
added to the sequence of existing steps (if any). For the
tidy method, a tibble with columns
columns that will be affected).
This operation may be useful for situations where a binary piece of information may need to be represented as categorical instead of numeric. For example, naive Bayes models would do better to have factor predictors so that the binomial distribution is modeled instead of a Gaussian probability density of numeric binary data. Note that the numeric data is only verified to be numeric (and does not count levels).
library(modeldata) data(covers) rec <- recipe(~ description, covers) %>% step_regex(description, pattern = "(rock|stony)", result = "rocks") %>% step_regex(description, pattern = "(rock|stony)", result = "more_rocks") %>% step_bin2factor(rocks) tidy(rec, number = 3)#> # A tibble: 1 x 2 #> terms id #> <chr> <chr> #> 1 rocks bin2factor_jcJSLrec <- prep(rec, training = covers) results <- bake(rec, new_data = covers) table(results$rocks, results$more_rocks)#> #> 0 1 #> yes 0 29 #> no 11 0tidy(rec, number = 3)#> # A tibble: 1 x 2 #> terms id #> <chr> <chr> #> 1 rocks bin2factor_jcJSL