K-fold Validation

K-Fold Validation is a resampling procedure in statistical model evaluation that partitions the dataset into K equally sized subsets, iteratively using each subset as a validation set while the remaining K−1 subsets form the training set, thereby enabling a robust assessment of model performance across different data splits.

1K

Publications

56.1K

Citations

3.9K

Authors

1.6K

Institutions

Publications per year

2017–2026

754

Variants

K-fold Cross ValidationK-fold Cross-validation

Authors

3.9K

  1. WA
    Waqas Ahmad

    COMSATS University Islamabad, Pakistan

    10 publications · 727 citations

    10

    h-index

  2. KK
    Kaffayatullah Khan

    King Faisal University, Saudi Arabia

    9 publications · 328 citations

    9

    h-index

  3. MN
    Muhammad Nasir Amin

    King Faisal University, Saudi Arabia

    9 publications · 316 citations

    9

    h-index

  4. AA
    Ayaz Ahmad

    COMSATS University Islamabad, Pakistan

    9 publications · 779 citations

    9

    h-index

  5. IA
    Imran Ashraf

    Yeungnam University, South Korea

    8 publications · 475 citations

    8

    h-index

1–5 of 3.9K

Venues

  1. IEEE Access

    22 publications · 1.3K citations

    20

    h-index

  2. Sensors

    25 publications · 935 citations

    17

    h-index

  3. Materials

    15 publications · 914 citations

    15

    h-index

  4. Scientific Reports

    20 publications · 682 citations

    14

    h-index

  5. PLoS ONE

    16 publications · 2.1K citations

    14

    h-index

1–5