Results 11 to 20 of about 3,742,082 (296)
Null distribution of some goodness of fit statistics for logistic regression [PDF]
, 1984 The null distribution moment and percentile properties of several goodness of fit statistics for logistic regression models are considered. Small sample approximations to the critical values of the statistics are evaluated for the case of a single ...
Al-Sarraf, Z, Young, D H
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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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, 2005 Tree induction methods and linear models are popular techniques for supervised learning tasks, both for the prediction of nominal classes and numeric values.
Hall, Mark A. +2 more
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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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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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Properties of estimators of parameters in logistic regression models [PDF]
, 1985 Properties of various types of estimators of the regression coefficients in linear logistic regression models are considered. The estimators include those based on maximum likelihood, minimum chi-square and weighted least squares.
Al-Sarraf, Z, Young, D H
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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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On Coresets for Logistic Regression
CoRR, 2018 Coresets are one of the central methods to facilitate the analysis of large data sets. We continue a recent line of research applying the theory of coresets to logistic regression. First, we show a negative result, namely, that no strongly sublinear sized coresets exist for logistic regression. To deal with intractable worst-case instances we introduce
Munteanu A. +3 more
openaire +8 more sources