process_y_functional: Process Outcome Input for Keras (Functional API)

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

Process Outcome Input for Keras (Functional API)

Description

Preprocesses outcome data (y) into a format suitable for Keras models built with the Functional API. Handles both regression (numeric) and classification (factor) outcomes, including one-hot encoding for classification, and supports multiple outputs.

Usage

process_y_functional(
  y,
  is_classification = NULL,
  class_levels = NULL,
  layer_blocks = NULL
)

Arguments

y	A vector or data frame of outcomes.
is_classification	Logical, optional. If TRUE, treats y as classification. If FALSE, treats as regression. If NULL (default), it's determined from is.factor(y).
class_levels	Character vector, optional. The factor levels for classification outcomes. If NULL (default), determined from levels(y).
layer_blocks	A named list of layer block functions, optional. Used to disambiguate a multi-column y between the "N independent named output heads" case (one block per column name, e.g. output_1, output_2) and the "single vector-valued output" case (e.g. multi-step regression, a single block named "output" with units = ncol(y)). If NULL (default, and for any caller that predates this parameter), the original per-column-split behavior is preserved.

Value

A list containing:

• y_proc: The processed outcome data (matrix or one-hot encoded array, or list of these for multiple outputs).

• is_classification: Logical, indicating if y was treated as classification.

• num_classes: Integer, the number of classes for classification, or NULL.

• class_levels: Character vector, the factor levels for classification, or NULL.

• multistep_info: For the single vector-valued output case only, a list with steps (integer vector) and vars (character vector) describing the structure of the outcome's columns. NULL otherwise.

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