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0551866 - ÚTIA 2023 RIV GB eng J - Journal Article
Adam, L. - Mácha, V. - Šmídl, Václav - Pevný, T.
General framework for binary classification on top samples.
Optimization Methods & Software. Roč. 37, č. 5 (2022), s. 1636-1667. ISSN 1055-6788. E-ISSN 1029-4937
R&D Projects: GA ČR GA18-21409S
Institutional support: RVO:67985556
Keywords : general framework * classification * ranking * accuracy at the top * Neyman–Pearson * Pat&Mat
OECD category: Applied mathematics
Impact factor: 2.2, year: 2022
Method of publishing: Open access
http://library.utia.cas.cz/separaty/2022/AS/smidl-0551866.pdf https://www.tandfonline.com/doi/full/10.1080/10556788.2021.1965601
Permanent Link: https://hdl.handle.net/11104/0337818