Setting decision thresholds when operating conditions are uncertain

DOI10.1007/s10618-019-00613-7zbMath1458.68163DBLPjournals/datamine/FerriHF19OpenAlexW2916251871WikidataQ62630508 ScholiaQ62630508MaRDI QIDQ2218341

José Hernández-Orallo, Peter A. Flach, César Ferri

Publication date: 15 January 2021

Published in: Data Mining and Knowledge Discovery (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10618-019-00613-7

zbMATH Keywords

classificationuncertaintycalibrationoperating conditionthreshold choice methods

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05)

Uses Software

• UCI-ml
• RWeka
• GitHub

Cites Work

• ROC curves in cost space
• Open-source machine learning: R meets Weka
• Measuring classifier performance: a coherent alternative to the area under the ROC curve
• PAV and the ROC convex hull
• Robust classification for imprecise environments
• Unnamed Item

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