Holdout Evaluation

Holdout Evaluation is a model validation technique in the evaluation of recommender systems that involves partitioning the dataset into distinct training and test sets to assess the model's predictive performance on unseen data.

48

Publications

3K

Citations

194

Authors

81

Institutions

Publications per year

2017–2026

28

Variants

Hold-out EvaluationHold-out MethodHoldout Method

Authors

194

  1. BD
    B D'Alessandro

    Canfield Scientific (United States), United States

    2 publications · 138 citations

    2

    h-index

  2. MH
    Moshe Handelsman

    Walden University, United States

    2 publications · 52 citations

    2

    h-index

  3. RH
    Rod Hook

    New York University, United States

    2 publications · 138 citations

    2

    h-index

  4. GB
    Gavin Buttimore

    Google (United States), United States

    2 publications · 40 citations

    2

    h-index

  5. AP
    Adrià Puigdomènech Badia

    Google (United States), United States

    2 publications · 40 citations

    2

    h-index

1–5 of 194

Venues

  1. arXiv (Cornell University)

    Repository · 5 publications · 197 citations

    5

    h-index

  2. Journal of Marketing Research

    3 publications · 219 citations

    3

    h-index

  3. IEEE Access

    2 publications · 193 citations

    2

    h-index

  4. Nucleic Acids Research

    1 publications · 154 citations

    1

    h-index

  5. Journal of Direct Marketing

    JDM · 1 publications · 34 citations

    1

    h-index

1–5