Metric Conformal Prediction via the Conditional Expected Local Radius
We introduce the conditional expected local radius (CELR) and develop a new conformal prediction method for non-Euclidean responses in general metric spaces. CELR measures local conditional probability concentration, allowing prediction sets to accommodate heterogeneity and multimodality without requiring densities or a vector space structure. Its conditional distribution yields a nonconformity score that is comparable across covariate values and avoids costly transport comparisons between distance profiles. We further adapt a metric distributional random forest that handles multivariate covariates and nonlinear interactions, while a single forest fit supplies all score components, reduci...
| Authors | Rui Qiu, Fang Yao, Zhou Yu |
|---|---|
| Primary category | stat.ML |
| Published | 22 October 2026 |
| Last updated at source | 22 October 2026 |
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