Results 11 to 20 of about 2,017,337 (259)
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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Barekeng, 2023 An understanding of factors that affect the recovery time from a disease is important for the community, medical staff, and also the government. This research analyzed factors that affect the recovery time of Covid-19 sufferers in West Sumatra.
Irvanal Haq +3 more
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TRANSFER LEARNING BASED ON LOGISTIC REGRESSION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015 In this paper we address the problem of classification of remote sensing images in the framework of transfer learning with a focus on domain adaptation.
A. Paul, F. Rottensteiner, C. Heipke
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Maximal Uncorrelated Multinomial Logistic Regression
IEEE Access, 2019 Multinomial logistic regression (MLR) has been widely used in the field of face recognition, text classification, and so on. However, the standard multinomial logistic regression has not yet stressed the problem of data redundancy.
Dajiang Lei +4 more
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Privacy-preserving logistic regression with secret sharing
BMC Medical Informatics and Decision Making, 2022 Background Logistic regression (LR) is a widely used classification method for modeling binary outcomes in many medical data classification tasks. Researchers that collect and combine datasets from various data custodians and jurisdictions can greatly ...
Ali Reza Ghavamipour +2 more
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High-dimensional Ising model selection using ${\ell_1}$-regularized logistic regression [PDF]
, 2010 We consider the problem of estimating the graph associated with a binary Ising Markov random field. We describe a method based on $\ell_1$-regularized logistic regression, in which the neighborhood of any given node is estimated by performing logistic ...
Lafferty, John D. +2 more
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BarekengThe Public Health Development Index (Indeks Pembangunan Kesehatan Masyarakat - IPKM) is a combined parameter that reflects progress in health development and is useful for determining areas that need assistance in improving health development.
Erwan Setiawan +2 more
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Multicollinearity in Logistic Regression Model -Subject Review- [PDF]
المجلة العراقية للعلوم الاحصائية, 2020 : The logistic regression model is one of the modern statistical methods developed to predict the set of quantitative variables (nominal or monotonous), and it is considered as an alternative test for the simple and multiple linear regression ...
Najlaa Saad Ibrahim +2 more
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