Calibrating Machine Learning Approaches for Probability Estimation Without Calibration Data

Eleonora Di Carluccio, Georgios Koliopanos, Francisco M. Ojeda, Christian Weimar, Andreas Ziegler

Open source

DOI: 10.1002/sim.70751
Published: 2026-10
Container: Statistics in Medicine
Publisher: Wiley
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1002/sim.70751,
  title = {Calibrating Machine Learning Approaches for Probability Estimation Without Calibration Data},
  author = {Eleonora Di Carluccio and Georgios Koliopanos and Francisco M. Ojeda and Christian Weimar and Andreas Ziegler},
  year = {2026},
  journal = {Statistics in Medicine},
  doi = {10.1002/sim.70751},
  url = {https://doi.org/10.1002/sim.70751}
}

RIS

TY  - JOUR
TI  - Calibrating Machine Learning Approaches for Probability Estimation Without Calibration Data
AU  - Eleonora Di Carluccio
AU  - Georgios Koliopanos
AU  - Francisco M. Ojeda
AU  - Christian Weimar
AU  - Andreas Ziegler
PY  - 2026
JO  - Statistics in Medicine
DO  - 10.1002/sim.70751
UR  - https://doi.org/10.1002/sim.70751
ER  -

APA

Carluccio, E. D., Koliopanos, G., Ojeda, F. M., Weimar, C., & Ziegler, A. (2026). Calibrating Machine Learning Approaches for Probability Estimation Without Calibration Data. Statistics in Medicine. https://doi.org/10.1002/sim.70751

Source records

crossref · retrieved 2026-11-10T19:28:23.712Z