Small Sample Overfitting
Small Sample Overfitting is a type of overfitting that occurs when a model learns spurious patterns or noise from a limited training dataset, leading to poor generalization on unseen data due to insufficient statistical power to reliably estimate model parameters.
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115
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2017–2026
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Does PLS Have Advantages for Small Sample Size or Non-Normal Data?1
Goodhue, Lewis ', Thompson · MIS Quarterly · 2012 · 601 citations
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Beijing University of Posts and Telecommunications
Beijing, China
4 h-index
13 publications
577 citations
University College London
London, United Kingdom
2 h-index
3 publications
86 citations

Lanzhou University of Technology
Lanzhou, China
2 h-index
6 publications
204 citations

Northwestern Polytechnical University
Xi'an, China
2 h-index
8 publications
1.3K citations

The University of Adelaide
Adelaide, Australia
2 h-index
3 publications
451 citations

University of Georgia
Athens, United States
1 h-index
1 publications
601 citations
ShanghaiTech University
Shanghai, China
1 h-index
1 publications
50 citations
University of Washington Tacoma
Tacoma, United States
1 h-index
1 publications
37 citations
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1 publications · 219 citations
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1 publications · 81 citations
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1 publications · 15 citations
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LNCS · Book series · 1 publications · 15 citations
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Repository · 1 publications · 11 citations
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