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, ...)
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
Not used by this step since no new variables are created.
A logical to indicate if the quantities for preprocessing have been estimated.
A character string that contains the names of
columns that should be removed. These values are not determined
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
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")#>  FALSEtidy(zv_filter, number = 1)#> # A tibble: 1 x 2 #> terms id #> <chr> <chr> #> 1 NA zv_mQoHJtidy(filter_obj, number = 1)#> # A tibble: 1 x 2 #> terms id #> <chr> <chr> #> 1 one_value zv_mQoHJ