Holdout Sample Evaluation
Holdout Sample Evaluation is a validation technique in revenue forecasting research that belongs to the broader class of out-of-sample evaluation methods, distinguished by its use of a temporally or randomly partitioned subset of observed data withheld from model training to provide an unbiased assessment of predictive accuracy.
32
Publications
5.8K
Citations
72
Authors
45
Institutions
Publications per year
2017–2026
7
Variants
Hold-out Sample Evaluation
Parents
32
Predictive model assessment in PLS-SEM: guidelines for using PLSpredict
Galit Shmueli, Marko Sarstedt, Joseph F. Hair et al. · European Journal of Marketing · 2019 · 3.8K citations
Using Neural Networks for Credit Scoring
Herbert L. Jensen · Managerial Finance · 1992 · 191 citations
1–5 of 32
72
2
h-index
2
h-index
The University of Texas at Austin, United States
2 publications · 170 citations
2
h-index
2
h-index
2
h-index
1–5 of 72
45

Universität Trier
Trier, Germany
2 h-index
8 publications
340 citations
University of Utah
Salt Lake City, United States
2 h-index
6 publications
748 citations

Griffith University
Brisbane, Australia
2 h-index
4 publications
91 citations
Universiti Putra Malaysia
Seri Kembangan, Malaysia
1 h-index
1 publications
3.8K citations
Suffolk University
Boston, United States
1 h-index
1 publications
34 citations
Walden University
Minneapolis, United States
1 h-index
1 publications
39 citations

California State University, Fullerton
Fullerton, United States
1 h-index
1 publications
191 citations
Boston University
Boston, United States
1 h-index
2 publications
68 citations
1–8 of 45
4 publications · 222 citations
4
h-index
JOFS · 2 publications · 44 citations
2
h-index
1 publications · 191 citations
1
h-index
1 publications · 310 citations
1
h-index
1 publications · 77 citations
1
h-index
1–5