Crossconformal predictive distributions
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Proceedings of the Seventh Workshop on Conformal and Probabilistic Prediction and Applications, PMLR 91:3751, 2018.
Abstract
Conformal predictive systems are a recent modification of conformal predictors that output, in regression problems, probability distributions for labels of test observations rather than set predictions. The extra information provided by conformal predictive systems may be useful, e.g., in decision making problems. Conformal predictive systems inherit the relative computational inefficiency of conformal predictors. In this paper we discuss two computationally efficient versions of conformal predictive systems, which we call split conformal predictive systems and crossconformal predictive systems, and discuss their advantages and limitations.
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