Confidence on the Focal: Conformal Prediction with Selection-Conditional Coverage

arXiv:2403.03868v1 Announce Type: cross
Abstract: Conformal prediction builds marginally valid prediction intervals which cover the unknown outcome of a randomly drawn new test point with a prescribed probability. In practice, a common scenario is that, after seeing the test unit(s), practitioners decide which test unit(s) to focus on in a data-driven manner, and wish to quantify the uncertainty for the focal unit(s). In such cases, marginally valid prediction intervals for these focal units can be misleading due to selection bias. …

abstract arxiv confidence coverage data data-driven focus math.st practice prediction probability stat.me stat.ml stat.th test the unknown type