Isotonic Regression
Isotonic Regression is a non-parametric regression technique that estimates a monotonic function by minimizing the squared error between observed responses and fitted values subject to the constraint that the predicted outputs are non-decreasing (or non-increasing) with respect to the input variables.
246
Publications
17.3K
Citations
512
Authors
236
Institutions
Publications per year
2017–2026
59
246
An empirical comparison of supervised learning algorithms
Rich Caruana, Alexandru Niculescu-Mizil · 2006 · 2.7K citations
Predicting good probabilities with supervised learning
Alexandru Niculescu-Mizil, Rich Caruana · 2005 · 1.6K citations
The Use of the Rank Transform in Regression
Ronald L. Iman, W. J. Conover · Technometrics · 1979 · 469 citations
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University of California, Berkeley, United States
5 publications · 261 citations
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Rutgers Sexual and Reproductive Health and Rights, Netherlands
5 publications · 129 citations
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Columbia University
New York, United States
11 h-index
20 publications
2.4K citations
University of Michigan
Ann Arbor, United States
10 h-index
18 publications
449 citations
National Institute of Environmental Health Sciences
Durham, United States
7 h-index
10 publications
443 citations
National Institutes of Health
Bethesda, United States
7 h-index
11 publications
705 citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
7 h-index
8 publications
632 citations
University of Missouri
Columbia, United States
6 h-index
7 publications
222 citations
Carnegie Mellon University
Pittsburgh, United States
6 h-index
9 publications
1.3K citations

Cornell University
Ithaca, United States
5 h-index
8 publications
9K citations
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15 publications · 876 citations
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20 publications · 973 citations
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15 publications · 1.1K citations
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Repository · 13 publications · 393 citations
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9 publications · 840 citations
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