Jackknife Validation

Jackknife Validation is a resampling technique in statistical validation that systematically omits individual observations from the dataset to assess the stability and robustness of an estimator by computing its value across subsamples formed through the sequential removal of single data points.

357

Publications

33K

Citations

1.1K

Authors

525

Institutions

Publications per year

2017–2026

83

Variants

Leave-one-out Cross-validation

Authors

1.1K

  1. YC
    Yu‐Dong Cai

    Shanghai University, China

    37 publications · 2.6K citations

    27

    h-index

  2. HL
    Hao Lin

    University of Electronic Science and Technology of China, China

    23 publications · 3.1K citations

    23

    h-index

  3. KC
    Kuo‐Chen Chou

    The Gordon Life Science Institute, United States

    23 publications · 4.2K citations

    23

    h-index

  4. WC
    Wei Chen

    North China University of Science and Technology, China

    23 publications · 2.9K citations

    22

    h-index

  5. HD
    Hui Ding

    University of Electronic Science and Technology of China, China

    14 publications · 1.9K citations

    14

    h-index

1–5 of 1.1K

Venues

  1. Protein and Peptide Letters

    21 publications · 1.1K citations

    18

    h-index

  2. PLoS ONE

    17 publications · 1.8K citations

    16

    h-index

  3. Proteins Structure Function and Bioinformatics

    13 publications · 890 citations

    13

    h-index

  4. Bioinformatics

    14 publications · 1.6K citations

    13

    h-index

  5. Molecular BioSystems

    8 publications · 875 citations

    8

    h-index

1–5