ReLogit: Rare Events Logistic Regression [PDF]
Journal of Statistical Software, 2003 We study rare events data, binary dependent variables with dozens to thousands of times fewer ones (events, such as wars, vetoes, cases of political activism, or epidemiological infections) than zeros ("nonevents").
Langche Zeng, Gary King, Michael Tomz
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Primer on binary logistic regression
Family Medicine and Community Health, 2021 Family medicine has traditionally prioritised patient care over research. However, recent recommendations to strengthen family medicine include calls to focus more on research including improving research methods used in the field.
Jenine K Harris
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Logistic regression: A simple primer
Cancer Research, Statistics, and Treatment, 2021 Logistic regression is used to obtain the odds ratio in the presence of more than one explanatory variable. This procedure is quite similar to multiple linear regression, with the only exception that the response variable is binomial.
Ankita Pal
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Fast binary logistic regression [PDF]
PeerJ Computer ScienceThis study presents a novel numerical approach that improves the training efficiency of binary logistic regression, a popular statistical model in the machine learning community.
Nurdan Ayse Saran, Fatih Nar
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Evaluating logistic regression and geographically weighted logistic regression models for predicting orange-fleshed sweet potato adoption intention in Benin [PDF]
Scientific ReportsThe low adoption rate of biofortified crops, like orange-fleshed sweet potatoes (OFSP), by farmers remains a major food security concern. Accurate forecasting models for OFSP adoption intention are essential for breeding and introduction projects.
Idrissou Ahoudou +8 more
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From Logistic Regression to Foundation Models: Factors Associated With Improved Forecasts [PDF]
CureusAbdulazeez Alabi +4 more
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Regression Analysis with Scikit-learn (part 2 - Logistic)
The Programming Historian, 2022 This lesson is the second in a two-part lesson focusing on regression analysis. It provides an overview of logistic regression, how to use Python (scikit-learn) to make a logistic regression model, and a discussion of interpreting the results of such ...
Matthew J. Lavin
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Two Statistical Approaches to Justify the Use of the Logistic Function in Binary Logistic Regression
Mathematical Problems in Engineering, 2023 Logistic regression is a commonly used classification algorithm in machine learning. It allows categorizing data into discrete classes by learning the relationship from a given set of labeled data.
A. Zaidi, A. S. A. Al Luhayb
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Logistic regression applied to natural hazards: rare event logistic regression with replications [PDF]
Natural Hazards and Earth System Sciences, 2012 Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead ...
M. Guns, V. Vanacker
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Applying logistic LASSO regression for the diagnosis of atypical Crohn's disease
Scientific Reports, 2022 In countries with a high incidence of tuberculosis, the typical clinical features of Crohn's disease (CD) may be covered up after tuberculosis infection, and the identification of atypical Crohn's disease and intestinal tuberculosis (ITB) is still a ...
Y. Li, Fanggen Lu, Yani Yin
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