Split-sample Validation

Split-Sample Validation is a validation protocol in which a dataset is partitioned into two distinct subsets—one used for model development or training and the other for independent evaluation—thereby enabling an assessment of the model’s generalizability while minimizing overfitting.

159

Publications

12.7K

Citations

728

Authors

308

Institutions

Publications per year

2017–2026

47

Variants

Holdout MethodHoldout Validation

Authors

728

  1. KL
    Ko Ling Chan

    University of Hong Kong, Hong Kong SAR China

    3 publications · 41 citations

    3

    h-index

  2. MP
    Michael Pencina

    Boston University, United States

    2 publications · 192 citations

    2

    h-index

  3. RE
    Raquel E. Gur

    University of Pennsylvania, United States

    2 publications · 466 citations

    2

    h-index

  4. BM
    B. McKeown

    The University of Texas Health Science Center at Tyler, United States

    2 publications · 245 citations

    2

    h-index

  5. KN
    Kathy N. Johnson

    Illinois Institute of Technology, United States

    2 publications · 157 citations

    2

    h-index

1–5 of 728

Venues

  1. PubMed

    Repository · 7 publications · 310 citations

    7

    h-index

  2. Psychological Reports

    4 publications · 122 citations

    4

    h-index

  3. Clinical Chemistry

    4 publications · 61 citations

    4

    h-index

  4. Journal of Conflict Resolution

    3 publications · 92 citations

    3

    h-index

  5. Journal of Clinical Psychology

    3 publications · 38 citations

    3

    h-index

1–5