Pandora's Regret is a closed-form pairwise scoring rule derived from expected optimal search costs that elicits true probabilities and outperforms log loss, accuracy, and F1 at predicting diagnostic costs on MedMNIST models.
The geometry of proper scoring rules
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A Kolmogorov-Nagumo mean-based framework for generalized g-conditional entropies represents Augustin-Csiszár cases beyond the scope of prior η-averaging methods.
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Pandora's Regret: A Proper Scoring Rule for Evaluating Sequential Search
Pandora's Regret is a closed-form pairwise scoring rule derived from expected optimal search costs that elicits true probabilities and outperforms log loss, accuracy, and F1 at predicting diagnostic costs on MedMNIST models.
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Kolmogorov--Nagumo Mean Frameworks for Conditional Entropy
A Kolmogorov-Nagumo mean-based framework for generalized g-conditional entropies represents Augustin-Csiszár cases beyond the scope of prior η-averaging methods.