WRSWorld Research StateContribute
WORLD RESEARCH STATE

Conformalized Quantile Regression for adaptive prediction intervals

Contribution grade

AI uncertainty, reliability and selective prediction · Human-designed research method or resource

Reference score140,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Fits lower and upper conditional quantiles on proper training data, then uses held-out signed interval errors to conformalize variable-width regression intervals.

Scientific scope

Fits lower and upper conditional quantiles on proper training data, then uses held-out signed interval errors to conformalize variable-width regression intervals. Finite-sample guarantee is marginal under exchangeability, not exact coverage at each covariate or arbitrary distribution drift. Quantile regression and conformal prediction are inherited; interval efficiency depends on the fitted quantiles and sample split.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Finite-sample guarantee is marginal under exchangeability, not exact coverage at each covariate or arbitrary distribution drift. Quantile regression and conformal prediction are inherited; interval efficiency depends on the fitted quantiles and sample split.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

Full scientific record · Browse contribution grades · Request a correction