Extract Model Residuals Using `feature_data` Objects — residuals,feature

Extract residuals from a machine learning model compared to a `feature_data` object.

Usage

# S4 method for class 'feature_data'
residuals(
  object,
  model,
  subset = c("all", "test", "train"),
  xprep = c("both", "scale", "transform", "none"),
  yprep = c("both", "scale", "transform", "none"),
  to_original_scale = FALSE,
  as_matrix = TRUE,
  ...
)

Arguments

object: A `feature_data` object.
model: A fitted model object.
subset: Subset of the `preproc` data set.
xprep: Character argument if transformed data ("transform"), scaled data ("scale" ), transformed and scaled data ("both") or original raw data ("none") are used for x.
yprep: Character argument if transformed data ("transform"), scaled data ("scale" ), transformed and scaled data ("both") or original raw data ("none") are used for y.
to_original_scale: Logical value to force re-transformation of predictions to the original scale.
as_matrix: logical TRUE if the function should return matrix, or a data frame or tibble otherwise.
...: Additional arguments (currently not used).

Value

A matrix or vector with the residuals.

Details

Currently only certain Keras models can be used as fitted models.