recipes (version 0.1.0)

step_center: Centering Numeric Data

Description

step_center creates a specification of a recipe step that will normalize numeric data to have a mean of zero.

Usage

step_center(recipe, ..., role = NA, trained = FALSE, means = NULL,
  na.rm = TRUE)

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 are affected by the step. See selections for more details.

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.

means

A named numeric vector of means. This is NULL until computed by prep.recipe.

na.rm

A logical value indicating whether NA values should be removed when averaging.

Value

An updated version of recipe with the new step added to the sequence of existing steps (if any).

Details

Centering data means that the average of a variable is subtracted from the data. step_center estimates the variable means from the data used in the training argument of prep.recipe. bake.recipe then applies the centering to new data sets using these means.

See Also

recipe prep.recipe bake.recipe

Examples

# NOT RUN {
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)

center_trans <- rec %>%
  step_center(carbon, contains("gen"), -hydrogen)

center_obj <- prep(center_trans, training = biomass_tr)

transformed_te <- bake(center_obj, biomass_te)

biomass_te[1:10, names(transformed_te)]
transformed_te
# }