recipes (version 0.2.0)

has_role: Role Selection

Description

has_role(), all_predictors(), and all_outcomes() can be used to select variables in a formula that have certain roles.

Similarly, has_type(), all_numeric(), and all_nominal() are used to select columns based on their data type. Nominal variables include both character and factor.

In most cases, the selectors all_numeric_predictors() and all_nominal_predictors(), which select on role and type, will be the right approach for users.

See selections for more details.

current_info() is an internal function.

All of these functions have have limited utility outside of column selection in step functions.

Usage

has_role(match = "predictor")
all_predictors()
all_numeric_predictors()
all_nominal_predictors()
all_outcomes()
has_type(match = "numeric")
all_numeric()
all_nominal()
current_info()

Arguments

match

A single character string for the query. Exact matching is used (i.e. regular expressions won't work).

Value

Selector functions return an integer vector.

current_info() returns an environment with objects vars and data.

Examples

# NOT RUN {
library(modeldata)
data(biomass)

rec <- recipe(biomass) %>%
  update_role(
    carbon, hydrogen, oxygen, nitrogen, sulfur,
    new_role = "predictor"
  ) %>%
  update_role(HHV, new_role = "outcome") %>%
  update_role(sample, new_role = "id variable") %>%
  update_role(dataset, new_role = "splitting indicator")

recipe_info <- summary(rec)
recipe_info

# Centering on all predictors except carbon
rec %>%
  step_center(all_predictors(), -carbon) %>%
  prep(training = biomass) %>%
  bake(new_data = NULL)

# }