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A tidyverse friendly way to plug WoE versions of a set of predictor variables against a given binary outcome.
add_woe(.data, outcome, ..., dictionary = NULL, prefix = "woe")A tibble with the original columns of .data plus the woe columns wanted.
A tbl. The data.frame to plug the new woe version columns.
The bare name of the outcome variable.
Bare names of predictor variables, passed as you would pass
variables to dplyr::select(). This means that you can use all the
helpers like starts_with() and matches().
A tbl. If NULL the function will build a dictionary with
those variables passed to .... You can pass a custom dictionary too,
see dictionary() for details.
A character string that will be the prefix to the resulting new variables.
You can pass a custom dictionary to add_woe(). It must have the exactly the
same structure of the output of dictionary(). One easy way to do this is to
tweak a output returned from it.
mtcars %>% add_woe("am", cyl, gear:carb)
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