Identification of miRNA biomarkers for breast cancer by combining ensemble regularized multinomial logistic regression and Cox regression [PDF]
BMC Bioinformatics, 2022 Background Breast cancer is one of the most common cancers in women. It is necessary to classify breast cancer subtypes because different subtypes need specific treatment.
Juntao Li, Hongmei Zhang, Fugen Gao
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Bayesian Lasso and multinomial logistic regression on GPU. [PDF]
PLoS ONE, 2017 We describe an efficient Bayesian parallel GPU implementation of two classic statistical models-the Lasso and multinomial logistic regression. We focus on parallelizing the key components: matrix multiplication, matrix inversion, and sampling from the ...
Rok Češnovar, Erik Štrumbelj
doaj +5 more sources
Minimum sample size for developing a multivariable prediction model using multinomial logistic regression. [PDF]
Stat Methods Med Res, 2023 Aims Multinomial logistic regression models allow one to predict the risk of a categorical outcome with > 2 categories. When developing such a model, researchers should ensure the number of participants ( n ) is appropriate relative to the number of ...
Pate A +6 more
europepmc +3 more sources
Modern contraceptive method utilization and determinant factors among women in Ethiopia: Multinomial logistic regression mini- EDHS-2019 analysis. [PDF]
Contracept Reprod Med, 2023 Background Globally, approximately 290,000 women between the ages of 15 and 49 died from pregnancy-related problems in 2014 alone, with these sub-Saharan Africa accounts for 65% (179,000) of the deaths.
Negash BT, Chekol AT, Wale MA.
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Factors associated with unmet need for family planning in sub-Saharan Africa: A multilevel multinomial logistic regression analysis. [PDF]
PLoS One, 2022 Background More than one out of every ten married women in the world, and one out of every five women in Africa, have unmet family planning needs.
Teshale AB.
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Maximal Uncorrelated Multinomial Logistic Regression [PDF]
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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Multiclass Classification by Sparse Multinomial Logistic Regression [PDF]
IEEE Transactions on Information Theory, 2021 In this paper we consider high-dimensional multiclass classification by sparse multinomial logistic regression. We propose first a feature selection procedure based on penalized maximum likelihood with a complexity penalty on the model size and derive the nonasymptotic bounds for misclassification excess risk of the resulting classifier.
Felix Abramovich +2 more
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Logistic Regression Multinomial for Arrhythmia Detection [PDF]
2016 IEEE 1st International Workshops on Foundations and Applications of Self* Systems (FAS*W), 2016 In this paper, we introduce a method based on logistics Regression multi-class as a classifier to provide a powerful and accurate insight into cardiac arrhythmia.
Behadada, Omar +4 more
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Urban-Rural Differences in Patterns and Associated Factors of Multimorbidity Among Older Adults in China: A Cross-Sectional Study Based on Apriori Algorithm and Multinomial Logistic Regression. [PDF]
Front Public Health, 2021 Introduction: Multimorbidity has become one of the key issues in the public health sector. This study aimed to explore the urban–rural differences in patterns and associated factors of multimorbidity in China and to provide scientific reference for the ...
Zhang C +9 more
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Distributed Parallel Sparse Multinomial Logistic Regression [PDF]
IEEE Access, 2019 Sparse Multinomial Logistic Regression (SMLR) is widely used in the field of image classification, multi-class object recognition, and so on, because it has the function of embedding feature selection during classification.
Dajiang Lei +4 more
doaj +2 more sources