Private Split

Private Split is a dataset partitioning methodology within machine learning that belongs to the class of data splitting techniques, distinguished by its enforcement of strict separation between private and public data subsets to prevent information leakage and ensure unbiased model evaluation.

7

Publications

311

Citations

20

Authors

11

Institutions

Publications per year

2017–2026

1

Authors

20

  1. AH
    Anita Harris

    Deakin University, Australia

    1 publications · 69 citations

    1

    h-index

  2. NS
    Neena Shah More

    Society for Nutrition Education and Health Action, India

    1 publications · 55 citations

    1

    h-index

  3. GA
    Glyn Alcock

    University College London, United Kingdom

    1 publications · 55 citations

    1

    h-index

  4. SM
    Sean McCartney

    University of Essex, United Kingdom

    1 publications · 11 citations

    1

    h-index

  5. TA
    Tanja A. J. Houweling

    Erasmus MC, Netherlands

    1 publications · 55 citations

    1

    h-index

1–5 of 20

Venues

  1. Philosophy & Social Criticism

    1 publications · 15 citations

    1

    h-index

  2. Politics & Society

    PAS · 1 publications · 49 citations

    1

    h-index

  3. Feminist Economics

    1 publications · 27 citations

    1

    h-index

  4. 1

    h-index

  5. BMC Pregnancy and Childbirth

    1 publications · 55 citations

    1

    h-index

1–5