Conformal Prediction via Regression-as-Classification

arXiv:2404.08168v1 Announce Type: new
Abstract: Conformal prediction (CP) for regression can be challenging, especially when the output distribution is heteroscedastic, multimodal, or skewed. Some of the issues can be addressed by estimating a distribution over the output, but in reality, such approaches can be sensitive to estimation error and yield unstable intervals.~Here, we circumvent the challenges by converting regression to a classification problem and then use CP for classification to obtain CP sets for regression.~To preserve the ordering of the …

abstract arxiv challenges classification cs.lg distribution error multimodal prediction reality regression stat.ml type via