Author

Masashi Sugiyama

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#machine learning Preprint Sep 2026

Bayes-Optimal BER and AUC: Estimation and Evaluation of Estimators

The FeeBee framework is extended, originally proposed for evaluating Bayes-error estimators, to the optimal BER and AUC, and the resulting procedure provides practical evaluation scores without requiring knowledge of the optimum.

Ryota Ushio, Takashi Ishida, Masashi Sugiyama · 0 citations