`stability_metric`

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Axis stability_metric on sub-layer L3_5_E_selected_features_post_selection (layer l3_5).

Sub-layer

L3_5_E_selected_features_post_selection

Axis metadata

Default: 'jaccard'
Sweepable: False
Status: operational

Operational status summary

Operational: 2 option(s)
Future: 0 option(s)

Options

`jaccard` – operational

Jaccard similarity over selection sets across origins.

L3.5.E stability metric jaccard.

This option configures the stability_metric axis on the L3_5_E_selected_features_post_selection sub-layer of L3.5; output is emitted under manifest.diagnostics/l3_5/L3_5_E_selected_features_post_selection/ alongside the other selected views.

When to use

Default stability metric; |A ∩ B| / |A ∪ B| is intuitive and bounded in [0, 1].

References

macroforecast design Part 4: ‘diagnostic layers default-off; non-blocking; produce JSON + matplotlib views attached to manifest.diagnostics/.’

Related options: kuncheva

Last reviewed 2026-05-05 by macroforecast author.

`kuncheva` – operational

Kuncheva-corrected stability index.

L3.5.E stability metric kuncheva.

This option configures the stability_metric axis on the L3_5_E_selected_features_post_selection sub-layer of L3.5; output is emitted under manifest.diagnostics/l3_5/L3_5_E_selected_features_post_selection/ alongside the other selected views.

When to use

Larger feature panels where Jaccard is biased toward 0; explicitly corrects for chance agreement.

References

macroforecast design Part 4: ‘diagnostic layers default-off; non-blocking; produce JSON + matplotlib views attached to manifest.diagnostics/.’
Kuncheva (2007) ‘A stability index for feature selection’, AIA proceedings.

Related options: jaccard