On Calibration of Ensemble-Based Credal Predictors

@article{Mortier2022OnCO,
  title={On Calibration of Ensemble-Based Credal Predictors},
  author={Thomas Mortier and Viktor Bengs and Eyke H{\"u}llermeier and Stijn Luca and Willem Waegeman},
  journal={ArXiv},
  year={2022},
  volume={abs/2205.10082}
}
In recent years, several classification methods that intend to quantify epistemic uncertainty have been proposed, either by producing predictions in the form of second-order distributions or sets of probability distributions. In this work, we focus on the latter, also called credal predictors, and address the question of how to evaluate them: What does it mean that a credal predictor represents epistemic uncertainty in a faithful manner? To answer this question, we refer to the notion of… 

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Credal ensembles of classifiers
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