step_zv
creates a specification of a recipe step
that will remove variables that contain only a single value.
step_zv( recipe, ..., role = NA, trained = FALSE, removals = NULL, skip = FALSE, id = rand_id("zv") ) # S3 method for step_zv tidy(x, ...)
recipe | A recipe object. The step will be added to the sequence of operations for this recipe. |
---|---|
... | One or more selector functions to choose which
variables that will be evaluated by the filtering. 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. |
removals | A character string that contains the names of
columns that should be removed. These values are not determined
until |
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. |
x | A |
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 terms
which
is the columns that will be removed.
library(modeldata) data(biomass) biomass$one_value <- 1 biomass_tr <- biomass[biomass$dataset == "Training",] biomass_te <- biomass[biomass$dataset == "Testing",] rec <- recipe(HHV ~ carbon + hydrogen + oxygen + nitrogen + sulfur + one_value, data = biomass_tr) zv_filter <- rec %>% step_zv(all_predictors()) filter_obj <- prep(zv_filter, training = biomass_tr) filtered_te <- bake(filter_obj, biomass_te) any(names(filtered_te) == "one_value")#> [1] FALSE#> # A tibble: 1 x 2 #> terms id #> <chr> <chr> #> 1 NA zv_mQoHJ#> # A tibble: 1 x 2 #> terms id #> <chr> <chr> #> 1 one_value zv_mQoHJ