Logistic Regression
Logistic Regression is a statistical classification model within the family of generalized linear models that employs a logistic function to model the probability of a binary outcome variable, distinguishing it by estimating the relationship between one or more independent variables and the log-odds of the outcome in the context of supervised learning and predictive modeling.
95.9K
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5.1M
Citations
370.7K
Authors
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2017–2026
40.2K
95.9K
Choice Reviews Online · 1990 · 35.7K citations
LIBLINEAR: A Library for Large Linear Classification
Rong-En Fan, Kai‐Wei Chang, Cho‐Jui Hsieh et al. · 2008 · 6.6K citations
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Mario Negri Institute for Pharmacological Research, Italy
111 publications · 6.3K citations
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University of California San Diego, United States
66 publications · 4K citations
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Harvard University
Cambridge, United States
172 h-index
5.9K publications
458.3K citations

Johns Hopkins University
Baltimore, United States
139 h-index
4.8K publications
313.4K citations
University of Michigan
Ann Arbor, United States
135 h-index
2.8K publications
207.2K citations
University of Washington
Seattle, United States
133 h-index
2.6K publications
208.7K citations

Brigham and Women's Hospital
Boston, United States
132 h-index
2.9K publications
268.8K citations

Karolinska Institutet
Stockholm, Sweden
123 h-index
3.5K publications
190.1K citations
University of California, San Francisco
San Francisco, United States
120 h-index
2.8K publications
201.6K citations
University of Pennsylvania
Philadelphia, United States
118 h-index
2.2K publications
146.4K citations
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3K publications · 143.6K citations
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JPH · 509 publications · 59K citations
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485 publications · 53.9K citations
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Repository · 3.3K publications · 127.6K citations
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AJE · 458 publications · 48.4K citations
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