General Variable Filter
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 class '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
tidy(smaller_set, number = 1)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.