Results 301 to 310 of about 840,245 (337)

Multinomial Logistic Regression

Nursing Research, 2002
When the dependent variable consists of several categories that are not ordinal (i.e., they have no natural ordering), the ordinary least square estimator cannot be used. Instead, a maximum likelihood estimator like multinomial logit or probit should be used.The purpose of this article is to understand the multinomial logit model (MLM) that uses ...
Chanyeong, Kwak, Alan, Clayton-Matthews
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Multinomial Logistic Regression Ensembles

Journal of Biopharmaceutical Statistics, 2013
This article proposes a method for multiclass classification problems using ensembles of multinomial logistic regression models. A multinomial logit model is used as a base classifier in ensembles from random partitions of predictors. The multinomial logit model can be applied to each mutually exclusive subset of the feature space without variable ...
Kyewon, Lee, Hongshik, Ahn, Hojin, Moon, Ralph L, Kodell, James J, Chen   +4 more
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Prediction of spontaneous coal combustion tendency using multinomial logistic regression

International Journal of Occupational Safety and Ergonomics, 2021
Spontaneous combustion of coal is a complex underground mining disaster, which mainly threats mine safety and efficiency. Several factors usually cause spontaneous combustion of coal, such as gas concentration, ventilation and coal properties.
Nilufer Kursunoglu, Maruf Gogebakan
semanticscholar   +1 more source

The toponymy of sporting venues: A multinomial logistic regression analysis of football stadium names

International Review for the Sociology of Sport, 2021
Extant scholarship on football stadium names is almost exclusively restricted to discussing naming rights deals as expressions of toponymic commodification.
M. Rusu
semanticscholar   +1 more source

Interpreting multinomial logistic regression [PDF]

Stata Technical Bulletin, 1994
Social and biological scientists widely use logit (logistic) regression to model binary dependent variables such as move/stay or live/die. Techniques for modeling multiple-category dependent variables are a relatively recent development, however. Asking Stata to perform multinomial logistic regression is easy; given a Y with three or more unordered ...
Hamilton, Lawrence C., Seyfrit, Carole L.   +1 more
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Multinomial logistic regression algorithm

Annals of the Institute of Statistical Mathematics, 1992
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Multinomial Logistic Regression Analysis

2017
The usage of mixed methods approach on qualitative data has been exemplified in this chapter. The chapter presents the relevance of using multinomial regression approach in the study and discusses its results. The chapter is insightful for readers looking forward to learning practical applications of quantitative techniques on qualitative data.
Nausheen Nizami, Narayan Prasad
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Multinomial Latent Logistic Regression for Image Understanding

IEEE Transactions on Image Processing, 2016
In this paper, we present multinomial latent logistic regression (MLLR), a new learning paradigm that introduces latent variables to logistic regression. By inheriting the advantages of logistic regression, MLLR is efficiently optimized using the second-order derivatives and provides effective probabilistic analysis on output predictions.
Zhe, Xu, Zhibin, Hong, Ya, Zhang, Junjie, Wu, Ah Chung, Tsoi, Dacheng, Tao   +5 more
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Comparative analysis using multinomial logistic regression

2014 2nd International Conference on Business and Information Management (ICBIM), 2014
Financial sustainability can be ensured through adopting financial control measures. Therefore it is necessary to examine whether an ULB has exercised financial controls during a particular year. In our paper we have examined whether an ULB has been able to exercise our designed financial controls. We have categorised the ULBs in “Financial Control and
Sidhakam Bhattacharyya, Gautam Bandyopadhyay   +1 more
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Pliable lasso for the multinomial logistic regression

Communications in Statistics - Theory and Methods, 2020
In this paper, we study the multinomial logistic regression with interactive effects. Our approach involves the implementation of the pliable lasso penalty which allows for estimating the main effects of the covariates X and an interaction effects ...
Theophilus Quachie Asenso, Hai Zhang, Yong Liang   +2 more
semanticscholar   +1 more source