Decision Thresholds
Decision Thresholds is a decision criterion in Bayesian Decision Theory that specifies the minimum posterior probability or likelihood ratio required to assign an observation to a particular class, thereby distinguishing it from alternative classification rules by balancing the costs and risks associated with different types of errors.
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Publications
25.6K
Citations
1.1K
Authors
532
Institutions
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2017–2026
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University College London
London, United Kingdom
6 h-index
17 publications
1.4K citations

Centre National de la Recherche Scientifique
Paris, France
6 h-index
16 publications
448 citations
University of California, Irvine
Irvine, United States
6 h-index
7 publications
200 citations
University of Oxford
Oxford, United Kingdom
5 h-index
24 publications
2.6K citations
Harvard University
Cambridge, United States
5 h-index
8 publications
639 citations
Stanford University
Stanford, United States
5 h-index
9 publications
265 citations
Duke University
Durham, United States
4 h-index
5 publications
378 citations

Pennsylvania State University
State College, United States
4 h-index
5 publications
584 citations
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7 publications · 6.9K citations
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