frame_edge_policy#

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Axis frame_edge_policy on sub-layer l2_e (layer l2).

Sub-layer#

l2_e

Axis metadata#

  • Default: 'truncate_to_balanced'

  • Sweepable: True

  • Status: operational

Operational status summary#

  • Operational: 4 option(s)

  • Future: 0 option(s)

Options#

truncate_to_balanced – operational#

Trim leading / trailing rows until every series is observed.

See truncate_to_balanced function page for full documentation + parameters + standalone usage. Standalone: mf.functions.truncate_to_balanced_clean.

drop_unbalanced_series – operational#

Drop predictor columns that aren’t observed across the full sample.

See drop_unbalanced_series function page for full documentation + parameters + standalone usage. Standalone: mf.functions.drop_unbalanced_series_clean.

keep_unbalanced – operational#

Keep the panel’s natural unbalanced shape.

Lets L4 estimators handle missingness directly. Required for some L4 families (LSTM/GRU/transformer) and for partial-data robustness studies.

When to use

Custom panels with intentional unbalanced structure; missing-data-robust models.

References

  • macroforecast design Part 2, L2: ‘preprocessing is the only layer with a strict A→B→C→D→E execution order; every cell follows the same pipeline.’

Related options: truncate_to_balanced, drop_unbalanced_series

Last reviewed 2026-05-04 by macroforecast author.

zero_fill_leading – operational#

Zero-fill leading missing predictor cells; preserve the rest.

See zero_fill_leading function page for full documentation + parameters + standalone usage. Standalone: mf.functions.zero_fill_leading_clean.