Predictive Model Selection
Predictive Model Selection is a model selection paradigm that belongs to the class of statistical model evaluation methods, distinguished by its focus on choosing models based on their out-of-sample predictive performance for categorical outcomes rather than goodness-of-fit or theoretical optimality criteria.
441
Publications
65.1K
Citations
1.3K
Authors
624
Institutions
Publications per year
2017–2026
112
441
Model Selection and Multimodel Inference
Technometrics · 2003 · 5.6K citations
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
Linear Model Selection by Cross-validation
Jun Shao · Journal of the American Statistical Association · 1993 · 1.7K citations
1–5 of 441
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University of Minnesota
Minneapolis, United States
8 h-index
10 publications
1.5K citations
University of California, Berkeley
Berkeley, United States
7 h-index
12 publications
1.1K citations
Yale University
New Haven, United States
7 h-index
7 publications
1.2K citations
Texas A&M University
College Station, United States
7 h-index
11 publications
471 citations
Carnegie Mellon University
Pittsburgh, United States
6 h-index
7 publications
2.2K citations
University of Kentucky
Lexington, United States
5 h-index
6 publications
2.6K citations

University of Toronto
Toronto, Canada
5 h-index
8 publications
2.2K citations

Centre National de la Recherche Scientifique
Paris, France
5 h-index
9 publications
580 citations
1–8 of 624
18 publications · 4.3K citations
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11 publications · 9.1K citations
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11 publications · 2K citations
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10 publications · 295 citations
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Repository · 9 publications · 1.4K citations
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