Temporal Cross-validation

Temporal Cross-Validation is a time-series validation technique that belongs to the class of cross-validation methods, distinguished by its sequential splitting of data into temporally ordered training and testing sets to prevent leakage of future information and to evaluate model performance under realistic temporal dependencies.

18

Publications

900

Citations

105

Authors

58

Institutions

Publications per year

2017–2026

11

Publications

18

1–5 of 18

Authors

105

  1. AC
    Andrea Critto

    Ca' Foscari University of Venice, Italy

    1 publications · 22 citations

    1

    h-index

  2. EM
    Ellen M. Mikkelsen

    Aarhus University Hospital, Denmark

    1 publications · 10 citations

    1

    h-index

  3. PT
    Patrick Thoral

    Amsterdam University Medical Centers, Netherlands

    1 publications · 39 citations

    1

    h-index

  4. KS
    Karen Schleeweis

    Rocky Mountain Research Station, United States

    1 publications · 21 citations

    1

    h-index

  5. EA
    Emily A. Berner

    Massachusetts General Hospital, United States

    1 publications · 24 citations

    1

    h-index

1–5 of 105

Venues

  1. Journal of Clinical Epidemiology

    1 publications · 18 citations

    1

    h-index

  2. Applied Intelligence

    1 publications · 23 citations

    1

    h-index

  3. Environmental Pollution

    1 publications · 90 citations

    1

    h-index

  4. Clinical Orthopaedics and Related Research

    1 publications · 24 citations

    1

    h-index

  5. Ecological Modelling

    1 publications · 192 citations

    1

    h-index

1–5