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.

330

Publications

25.6K

Citations

1.1K

Authors

532

Institutions

Publications per year

2017–2026

95

Authors

1.1K

  1. RB
    Rafał Bogacz

    University of Oxford, United Kingdom

    4 publications · 599 citations

    4

    h-index

  2. MS
    Mathini Sellathurai

    Heriot-Watt University, United Kingdom

    4 publications · 290 citations

    4

    h-index

  3. PB
    Peter Brown

    University College London, United Kingdom

    3 publications · 401 citations

    3

    h-index

  4. KR
    Krishna R. Pattipati

    University of Connecticut, United States

    3 publications · 183 citations

    3

    h-index

  5. DM
    Damian M. Herz

    University of Oxford, United Kingdom

    3 publications · 401 citations

    3

    h-index

1–5 of 1.1K

Venues

  1. Clinical Chemistry

    7 publications · 6.9K citations

    7

    h-index

  2. IEEE Transactions on Signal Processing

    6 publications · 278 citations

    6

    h-index

  3. IEEE Transactions on Wireless Communications

    4 publications · 114 citations

    4

    h-index

  4. JAMA

    3 publications · 80 citations

    3

    h-index

  5. 3

    h-index

1–5