step_bin2factor {recipes} | R Documentation |
step_bin2factor
creates a specification of a recipe step that
will create a two-level factor from a single dummy variable.
step_bin2factor(recipe, ..., role = NA, trained = FALSE, levels = c("yes", "no"), columns = NULL)
recipe |
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 |
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. |
levels |
A length 2 character string that indicate the factor levels for the 1's (in the first position) and the zeros (second) |
columns |
A vector with the selected variable names. This is
|
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 in stead 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).
An updated version of recipe
with the
new step added to the sequence of existing steps (if any).
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) rec <- prep(rec, training = covers) results <- bake(rec, newdata = covers) table(results$rocks, results$more_rocks)