step_rm: General Variable Filter

Description Usage Arguments Value Examples

View source: R/rm.R

Description

step_rm creates a specification of a recipe step that will remove variables based on their name, type, or role.

Usage

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step_rm(
  recipe,
  ...,
  role = NA,
  trained = FALSE,
  removals = NULL,
  skip = FALSE,
  id = rand_id("rm")
)

## S3 method for class 'step_rm'
tidy(x, ...)

Arguments

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 selections() for more details. For the tidy method, these are not currently used.

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 prep.recipe() is called.

skip

A logical. Should the step be skipped when the recipe is baked by bake.recipe()? While all operations are baked when prep.recipe() is run, some operations may not be able to be conducted on new data (e.g. processing the outcome variable(s)). Care should be taken when using skip = TRUE as it may affect the computations for subsequent operations

id

A character string that is unique to this step to identify it.

x

A step_rm object.

Value

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.

Examples

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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)

Example output

Loading required package: dplyr

Attaching package:dplyrThe following objects are masked frompackage:stats:

    filter, lag

The following objects are masked frompackage:base:

    intersect, setdiff, setequal, union


Attaching package:recipesThe following object is masked frompackage:stats:

    step

# 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_WkgU7
2 oxygen   rm_WkgU7
3 nitrogen rm_WkgU7

recipes documentation built on April 16, 2021, 5:09 p.m.