preprocess_functions function

Examples of preprocess_fn functions

lifecycle::badge("experimental")

Examples of preprocess functions that can be used in cross_validate_fn() and validate_fn(). They can either be used directly or be starting points.

The examples use recipes, but you can also use caret::preProcess() or similar functions.

In these examples, the preprocessing will only affect the numeric predictors.

You may prefer to hardcode a formula like "y ~ ." (where y is your dependent variable) as that will allow you to set preprocess_one to TRUE in cross_validate_fn()

and validate_fn() and save time.

preprocess_functions(name)

Arguments

• name: Name of preprocessing function as it appears in the following list:

  Name	Description
  "standardize"	Centers and scales the numeric predictors
  "range"	Normalizes the numeric predictors to the 0-1 range
  "scale"	Scales the numeric predictors to have a standard deviation of one
  "center"	Centers the numeric predictors to have a mean of zero
  "warn"	Identity function that throws a warning and a message

Returns

A function with the following form:

function(train_data, test_data, formula, hyperparameters) {

``# Preprocess train_data and test_data

``# Return a list with the preprocessed datasets

``# and optionally a data frame with preprocessing parameters

``list(

``"train" = train_data,

``"test" = test_data,

``"parameters" = tidy_parameters

``)

}

See Also

Other example functions: model_functions(), predict_functions(), update_hyperparameters()

Author(s)

Ludvig Renbo Olsen, r-pkgs@ludvigolsen.dk