step_sequence: Build a Sliding Window of Predictors for Sequence Models

In kerasnip: A Bridge Between 'keras' and 'tidymodels'

Build a Sliding Window of Predictors for Sequence Models

Description

step_sequence() creates a specification of a recipe step that converts one or more ordered numeric predictor columns into a single list-column of ⁠(timesteps, features)⁠ matrices, one per row. This is the shape expected by recurrent layer blocks (e.g. keras3::layer_lstm(), keras3::layer_gru()) used with create_keras_functional_spec() or create_keras_sequential_spec().

Usage

step_sequence(
  recipe,
  ...,
  timesteps,
  role = "predictor",
  trained = FALSE,
  columns = NULL,
  new_col = "sequence_matrix",
  padding = c("drop", "zero"),
  skip = FALSE,
  id = recipes::rand_id("sequence")
)

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 (already time-ordered) numeric variables are windowed. See ⁠[selections()]⁠ for more details. All selected columns become "features" in the resulting window. For the tidy method, these are not currently used.
timesteps	A single integer. The sliding window length (number of past rows, including the current one) to include in each window.
role	For model terms created by this step, what analysis role should they be assigned?. By default, the new column is used as a predictor.
trained	A logical to indicate if the quantities for preprocessing have been estimated.
columns	A character string of the selected variable names. This is NULL until the step is trained by ⁠[prep.recipe()]⁠.
new_col	A character string for the name of the new list-column. The default is "sequence_matrix".
padding	One of "drop" (default) or "zero". Rows without a full timesteps history need special handling: "drop" removes them from the data (as ⁠[recipes::step_naomit()]⁠ does), while "zero" left-pads the missing history with rows of zeros so no rows are dropped.
skip	A logical. Should the step be skipped when the recipe is baked by ⁠[bake.recipe()]⁠? While all operations are baked when prep is run, skipping when bake is run may be other times when it is desirable to skip a processing step.
id	A character string that is unique to this step to identify it.

Value

An updated version of recipe with the new step added to the sequence of existing steps (if any). For the tidy method, a tibble with columns terms (the selected column names), value (the name of the destination list-column), timesteps, and id (the step identifier).

Examples

library(recipes)

dat <- data.frame(x1 = 1:10, x2 = 11:20, y = 1:10)

rec <- recipe(y ~ ., data = dat) %>%
  step_sequence(x1, x2, timesteps = 3, new_col = "window") %>%
  prep()

bake(rec, new_data = NULL)

kerasnip documentation built on Sept. 4, 2026, 1:06 a.m.