Cross-validation Studies
Cross-Validation Studies is a methodological framework in computational statistics that systematically partitions genomic and nonparametric data into complementary subsets to evaluate the predictive performance and generalizability of statistical models by iteratively training and testing across different folds.
1.4K
Publications
141.9K
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4.9K
Authors
1.8K
Institutions
Publications per year
2017–2026
438
1.4K
A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection
Ron Kohavi · 1995 · 10.7K citations · Full text
A survey of cross-validation procedures for model selection
2009 · 3.8K citations
A survey of cross-validation procedures for model selection
Statistics Surveys · 2010 · 3.3K citations · Full text
Predicting basal metabolic rate, new standards and review of previous work.
Schofield Wn · PubMed · 1985 · 2.9K citations
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Chinese Academy of Sciences
Beijing, China
15 h-index
53 publications
4.8K citations
University College London
London, United Kingdom
14 h-index
34 publications
14.2K citations
University of California, Los Angeles
Los Angeles, United States
12 h-index
30 publications
1.9K citations

Centre National de la Recherche Scientifique
Paris, France
12 h-index
28 publications
1.1K citations
Stanford University
Stanford, United States
12 h-index
22 publications
13.5K citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
11 h-index
27 publications
827 citations
University of California, Davis
Davis, United States
11 h-index
14 publications
699 citations

Cornell University
Ithaca, United States
11 h-index
36 publications
3.9K citations
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27 publications · 2.1K citations
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27 publications · 1.5K citations
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Repository · 22 publications · 3.9K citations
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18 publications · 4.2K citations
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17 publications · 997 citations
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