add_white_noise: Add White Noise to Encoded Predictor

In collinear: Automated Multicollinearity Management

Add White Noise to Encoded Predictor

Description

Internal function to add white noise to a encoded predictor to reduce the risk of overfitting when used in a model along with the response.

Usage

add_white_noise(
  df = NULL,
  response = NULL,
  predictor = NULL,
  white_noise = 0,
  seed = 1
)

Arguments

df	(required; data frame, tibble, or sf) A data frame with responses and predictors. Default: NULL.
response	(optional, character string) Name of a numeric response variable in df. Default: NULL.
predictor	(required, string) Name of a target-encoded predictor. Default: NULL
white_noise	(optional; numeric vector) Argument of the methods "mean", "rank", and "loo". Maximum white noise to add, expressed as a fraction of the range of the response variable. Range from 0 to 1. Default: 0.
seed	(optional; integer vector) Random seed to facilitate reproducibility when white_noise is not 0. If NULL, the function selects one at random, and the selected seed does not appear in the encoded variable names. Default: 0

Value

data frame

See Also

Other target_encoding_tools: encoded_predictor_name()

collinear documentation built on April 12, 2025, 1:36 a.m.