Add risk-controlling prediction sets - #30
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sgreenbury wants to merge 4 commits into
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sgreenbury wants to merge 4 commits into
sgreenbury wants to merge 4 commits into
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Introduce bounded-loss RCPS calibration with a Hoeffding upper confidence bound and per-example coverage loss. Support asymmetric scaled intervals and raw ensemble forecasts through quantile or standard-deviation interval families. Configure alpha and delta grids before calibration so fitted scales and prediction axes are explicit. Keep structural loss and bound contracts open to future extensions, and document per-pair guarantees alongside the existing conformal approaches.
Use semantic tensor aliases in the risk-loss interface and document the ensemble CP and RCPS APIs side by side. Add a regression test for the expected relationship between confidence level and fitted scale.
sgreenbury
marked this pull request as ready for review
August 11, 2026 14:12
Keep the additive Hoeffding term on the same display-math line so Markdown renderers do not interpret its leading plus sign as markup.
Clarify that scaled-interval inputs contain a centre and non-negative distances from it, rather than interval endpoints.
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Summary
Testing
uv run pytest --maxfail=3uv run prek run --hook-stage manual --all-filesCloses #22