step_rm
creates a specification of a recipe step
that will remove variables based on their name, type, or role.
step_rm( recipe, ..., role = NA, trained = FALSE, removals = NULL, skip = FALSE, id = rand_id("rm") ) # S3 method for step_rm 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 bake. 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_tr <- biomass[biomass$dataset == "Training",] biomass_te <- biomass[biomass$dataset == "Testing",] rec <- recipe(HHV ~ carbon + hydrogen + oxygen + nitrogen + sulfur, data = biomass_tr) library(dplyr) smaller_set <- rec %>% step_rm(contains("gen")) smaller_set <- prep(smaller_set, training = biomass_tr) filtered_te <- bake(smaller_set, biomass_te) filtered_te#> # A tibble: 80 x 3 #> carbon sulfur HHV #> <dbl> <dbl> <dbl> #> 1 46.4 0.22 18.3 #> 2 43.2 0.34 17.6 #> 3 42.7 0.3 17.2 #> 4 46.4 0.5 18.9 #> 5 48.8 0 20.5 #> 6 44.3 0.2 18.5 #> 7 38.9 0.51 15.1 #> 8 42.1 0.2 16.2 #> 9 29.2 4.9 11.1 #> 10 27.8 1.05 10.8 #> # … with 70 more rows#> # A tibble: 3 x 2 #> terms id #> <chr> <chr> #> 1 hydrogen rm_NJe2n #> 2 oxygen rm_NJe2n #> 3 nitrogen rm_NJe2n