Decision Threshold Optimization
Decision Threshold Optimization is a Bayesian diagnostic method that systematically determines the optimal cutoff point for classifying posterior probabilities by balancing misclassification costs and diagnostic accuracy within decision-theoretic frameworks.
146
Publications
5.9K
Citations
427
Authors
208
Institutions
Publications per year
2017–2026
42
146
Decision feedback equalization
C.A. Belfiore, J.H. Park · Proceedings of the IEEE · 1979 · 409 citations
Finding the Best Classification Threshold in Imbalanced Classification
Quan Zou, Sifa Xie, Ziyu Lin et al. · Big Data Research · 2016 · 282 citations
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Ningbo University
Ningbo, China
4 h-index
11 publications
299 citations

Xidian University
Xi'an, China
4 h-index
16 publications
709 citations
Virginia Tech
Blacksburg, United States
3 h-index
4 publications
145 citations

Centre National de la Recherche Scientifique
Paris, France
3 h-index
5 publications
381 citations

University of Electronic Science and Technology of China
Chengdu, China
3 h-index
7 publications
466 citations

University of Macau
Macao, Macao
3 h-index
12 publications
415 citations
University of California, Los Angeles
Los Angeles, United States
3 h-index
6 publications
217 citations
Nanyang Technological University
Singapore, Singapore
3 h-index
4 publications
110 citations
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4 publications · 111 citations
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4 publications · 207 citations
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JCIM · 2 publications · 197 citations
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2 publications · 52 citations
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2 publications · 89 citations
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