polynomial_expansion – Alias for polynomial – explicit expansion node in cascade pipelines.#

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Operational op under axis op, sub-layer L3_A_step_op, layer l3. Standalone callable: mf.functions.polynomial_expansion_transform.

Function signature#

mf.functions.polynomial_expansion_transform(
    panel: pd.DataFrame,
    degree: int,
) -> pd.DataFrame

Parameters#

name

type

default

constraint

description

panel

pd.DataFrame

—

—

Input panel. Each column is a variable; rows are time periods. Series is promoted to a single-column DataFrame internally.

degree

int

2

>= 1

Maximum polynomial degree. Degree 1 returns the panel unchanged; degree 2 appends _pow2 columns; etc.

Returns#

pd.DataFrame — scalar result.

Behavior#

Identical to polynomial but with a name that reads more clearly as a stage in a multi-step expansion pipeline.

When to use

Pipelines that explicitly stage expand → reduce sequences.

In recipe context#

Set params.op = "polynomial_expansion" in the relevant layer to activate this op within a recipe:

# Layer L3 recipe fragment
params:
  op: polynomial_expansion

References#

  • macroforecast design Part 2, L3: ‘feature engineering is a DAG of typed transforms; cascade-depth bounds the longest chain at cascade_max_depth.’