Decision Threshold Selection

Decision Threshold Selection is a methodological process in binary classification systems that determines the optimal cutoff point for distinguishing positive from negative instances by balancing sensitivity and specificity to minimize false positive rates.

222

Publications

12.8K

Citations

730

Authors

357

Institutions

Publications per year

2017–2026

61

Authors

730

  1. YL
    Youming Li

    Ningbo University, China

    3 publications · 74 citations

    3

    h-index

  2. MJ
    Ming Jin

    Ningbo University, China

    3 publications · 74 citations

    3

    h-index

  3. MM
    Mario Muštra

    University of Zagreb, Croatia

    2 publications · 90 citations

    2

    h-index

  4. KD
    Krešimir Delač

    University of Zagreb, Croatia

    2 publications · 90 citations

    2

    h-index

  5. HZ
    Hao Zhang

    Jilin University, China

    2 publications · 39 citations

    2

    h-index

1–5 of 730

Venues

  1. PLoS ONE

    6 publications · 265 citations

    6

    h-index

  2. IET Communications

    4 publications · 60 citations

    4

    h-index

  3. IEEE Communications Letters

    4 publications · 106 citations

    4

    h-index

  4. IEEE Access

    3 publications · 219 citations

    3

    h-index

  5. Medical Decision Making

    MDM · 3 publications · 168 citations

    3

    h-index

1–5