Target Strangeness: A Novel Conformal Prediction Difficulty Estimator

Alexis Bose; Jonathan Ethier; Paul Guinand

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arXiv · 2410.19077

Target Strangeness: A Novel Conformal Prediction Difficulty Estimator

Alexis Bose·Jonathan Ethier·Paul Guinand

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Abstract

This paper introduces Target Strangeness, a novel difficulty estimator for conformal prediction (CP) that offers an alternative approach for normalizing prediction intervals (PIs). By assessing how atypical a prediction is within the context of its nearest neighbours' target distribution, Target Strangeness can surpass the current state-of-the-art performance. This novel difficulty estimator is evaluated against others in the context of several conformal regression experiments.

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Alexis Bose, Jonathan Ethier, Paul Guinand. 2024-10-24. Target Strangeness: A Novel Conformal Prediction Difficulty Estimator. https://arxiv.org/abs/2410.19077

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