Model Selection
Model Selection is the process of identifying the most appropriate statistical or mathematical framework among a set of candidate models that best balances explanatory power, predictive accuracy, and parsimony for a given dataset and research question within a specified modeling domain.
3.4K
Publications
527.8K
Citations
6.6K
Authors
2.2K
Institutions
Publications per year
2017–2026
813
3.4K
Kenneth P. Burnham, David R. Anderson · Sociological Methods & Research · 2004 · 11.6K citations
A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection
Ron Kohavi · 1995 · 10.7K citations · Full text
Bradley Efron, Trevor Hastie, Iain M. Johnstone et al. · The Annals of Statistics · 2004 · 9.5K citations · Full text
1–5 of 3.4K
6.6K
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2.2K
Stanford University
Stanford, United States
35 h-index
96 publications
113.3K citations
University of Wisconsin–Madison
Madison, United States
30 h-index
59 publications
17.6K citations
University of California, Davis
Davis, United States
29 h-index
57 publications
10.9K citations

University of Minnesota
Minneapolis, United States
27 h-index
58 publications
14.8K citations
University of Oxford
Oxford, United Kingdom
23 h-index
55 publications
7.6K citations

Australian National University
Canberra, Australia
23 h-index
42 publications
2.7K citations
KU Leuven
Leuven, Belgium
23 h-index
53 publications
4.9K citations
Duke University
Durham, United States
22 h-index
45 publications
10.3K citations
1–8 of 2.2K
120 publications · 26.4K citations
69
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CSDA · 83 publications · 4.7K citations
38
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60 publications · 19.6K citations
38
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60 publications · 15.9K citations
36
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53 publications · 17K citations
34
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