Results 21 to 30 of about 4,991,757 (343)
Logistic Regression in Medical Research
Anesthesia and Analgesia, 2021 KEY POINT: Logistic regression is used to estimate the relationship between one or more independent variables and a binary (dichotomous) outcome variable.
P. Schober, T. Vetter
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A three-parameter logistic regression model
Statistical Theory and Related Fields, 2021 Dose–response experiments and data analyses are often carried out according to an optimal design under a model assumption. A two-parameter logistic model is often used because of its nice mathematical properties and plausible stochastic response ...
Xiaoli Yu, Shaoting Li, Jiahua Chen
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Loan classification using logistic regression
Informatika, 2023 Objectives. The studied problem of loan classification is particularly important for financial institutions, which must efficiently allocate monetary assets between entities as part of the provision of financial services.
U. I. Behunkou, M. Y. Kovalyov
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Predicting Heart Disease using Logistic Regression
Knowledge Engineering and Data Science, 2022 A common risk of death is caused by heart disease. It is critical in the field of medicine to be able to diagnose cardiac disease in order to adequately prevent and treat patients.
Mochammad Anshori, M. Syauqi Haris
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Predicting Type 2 Diabetes Using Logistic Regression and Machine Learning Approaches
International Journal of Environmental Research and Public Health, 2021 Diabetes mellitus is one of the most common human diseases worldwide and may cause several health-related complications. It is responsible for considerable morbidity, mortality, and economic loss.
Ram Joshi, Chandra Dhakal
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Fuzzy Semi-Parametric Logistic Quantile Regression Model
Wasit Journal for Pure Sciences, 2023 In this paper, the fuzzy semi-parametric logistic quantile regression model was studied in the absence of special conditions in the classical regression models.
Ahmed Razzaq, Ayad H. shemaila
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Malicious URL Detection using Logistic Regression
Coins, 2021 One of the major challenges faced by the Internet in the present day is to deal with achieving web security from ever-rising diverse types of threats.
Rupa Chiramdasu +4 more
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Bayesian logistic regression for presence-only data [PDF]
, 2015 Presence-only data are referred to situations in which a censoring mechanism acts on a binary response which can be partially observed only with respect to one outcome, usually denoting the \textit{presence} of an attribute of interest. A typical example
Antti Pettinen +3 more
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Privacy-preserving logistic regression training
BMC Medical Genomics, 2018 Background Logistic regression is a popular technique used in machine learning to construct classification models. Since the construction of such models is based on computing with large datasets, it is an appealing idea to outsource this computation to a
Charlotte Bonte, Frederik Vercauteren
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Bayesian Logistic Regression Model for Sub-Areas
Stats, 2023 Many population-based surveys have binary responses from a large number of individuals in each household within small areas. One example is the Nepal Living Standards Survey (NLSS II), in which health status binary data (good versus poor) for each ...
Lu Chen, Balgobin Nandram
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