A classification-integrated conformal framework for zero-inflated outcomes that guarantees marginal coverage and asymptotic minimal length under exchangeability, independent of the underlying models.
arXiv preprint arXiv:1805.09460 , year=
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
verdicts
UNVERDICTED 2roles
background 1polarities
background 1representative citing papers
Pith review generated a malformed one-line summary.
citing papers explorer
-
Classification-Powered Conformal Inference for Zero-inflated Outcomes
A classification-integrated conformal framework for zero-inflated outcomes that guarantees marginal coverage and asymptotic minimal length under exchangeability, independent of the underlying models.
-
A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification
Pith review generated a malformed one-line summary.