step_group_normalize: Group normalization
In mlverse/tft: Implementation of Temporal Fusion Transformer

step_group_normalize

R Documentation

Group normalization

Description

recipes::recipe() step for normalizing data per group. Most of the times we want to normalize each time series independently as they might have different scales.

Usage

step_group_normalize(
  recipe,
  ...,
  groups,
  stats = NULL,
  role = NA,
  trained = FALSE,
  skip = FALSE,
  id = recipes::rand_id("group_normalize")
)

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 variables for this step. See `selections()` for more details.
`groups`	<`tidy-select`> Columns to group by before computing normalization statistics.
`stats`	Is modified by `prep`. A data frame containing one row per distinct group, containing the normalization statistics.
`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.
`skip`	A logical. Should the step be skipped when the recipe is baked by `bake()`? While all operations are baked when `prep()` is run, some operations may not be able to be conducted on new data (e.g. processing the outcome variable(s)). Care should be taken when using `skip = TRUE` as it may affect the computations for subsequent operations.
`id`	A character string that is unique to this step to identify it.