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.
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2017–2026
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K-fold Cross ValidationK-fold Cross-validation
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Machine learning algorithm validation with a limited sample size
Andrius Vabalas, Emma Gowen, Ellen Poliakoff et al. · PLoS ONE · 2019 · 1.7K citations · Full text
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COMSATS University Islamabad
Islamabad, Pakistan
15 h-index
15 publications
1K citations

Chinese Academy of Sciences
Beijing, China
11 h-index
12 publications
857 citations
King Faisal University
Hofuf, Saudi Arabia
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10 publications
359 citations
Future University in Egypt
Cairo, Egypt
9 h-index
9 publications
408 citations
Prince Sattam Bin Abdulaziz University
Al Kharj, Saudi Arabia
9 h-index
9 publications
684 citations
Seoul National University
Seoul, South Korea
8 h-index
8 publications
928 citations

Yeungnam University
Daegu, South Korea
8 h-index
8 publications
475 citations

National Yang Ming Chiao Tung University
Hsinchu, Taiwan
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8 publications
564 citations
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