Results 311 to 320 of about 840,245 (337)

Multinomial Logistic Regression (55 Patients)

2012
Primary question: the numbers of patients falling out of bed with and without injury are assessed in two hospital departments. It is expected that the department of internal medicine will have higher scores.
Ton J. Cleophas, Aeilko H. Zwinderman
openaire   +1 more source

Sentiment analysis using multinomial logistic regression

2017 International Conference on Control, Electronics, Renewable Energy and Communications (ICCREC), 2017
Data amount becomes rapidly increased in today's era. Data can be in form of text, picture, voice, and video. Social media is one factor of the data increase as everybody expresses, gives opinion, and even complains in social media. The first step is data collection used API twitter with each candidate names on Jakarta Governor Election.
W.P. Ramadhan, S.T.M.T. Astri Novianty, S.T.M.T. Casi Setianingsih   +2 more
openaire   +1 more source

Hate Speech Detection on Twitter Using Multinomial Logistic Regression Classification Method

International Conference on Internet of Things and Intelligence System, 2019
In today's social media, especially Twitter is very important for the success and destruction of one's image due to the many sentences of opinion that can compete the users. Examples of phrases that mean evil refer to hate speech to others.
Purnama Sari Br Ginting, Budhi Irawan, C. Setianingsih   +2 more
semanticscholar   +1 more source

A general robust low–rank multinomial logistic regression for corrupted matrix data classification

Applied intelligence (Boston), 2023
Yuyu Hu, Yali Fan, Yan Song, Ming Li
semanticscholar   +1 more source

A mixed‐effects multinomial logistic regression model

Statistics in Medicine, 2003
AbstractA mixed‐effects multinomial logistic regression model is described for analysis of clustered or longitudinal nominal or ordinal response data. The model is parameterized to allow flexibility in the choice of contrasts used to represent comparisons across the response categories.
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Classification Efficiency of Multinomial Logistic Regression Relative to Ordinal Logistic Regression

Journal of the American Statistical Association, 1989
Abstract Classification procedures are useful for the prediction of a response (or outcome) as a result of knowledge of the levels of one or more independent (or predictor) variables. The procedure is said to classify the (possibly multivariate) observation to a level of the response variable. An example might be the prediction of whether an individual
M. Karen Campbell, Allan Donner
openaire   +1 more source

Multinomial Logistic Regression

2023
Kamarul Imran Musa, Wan Nor Arifin Wan Mansor, Tengku Muhammad Hanis   +2 more
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A Goodness‐of‐Fit Test for Multinomial Logistic Regression

Biometrics, 2006
Summary This article presents a score test to check the fit of a logistic regression model with two or more outcome categories. The null hypothesis that the model fits well is tested against the alternative that residuals of samples close to each other in covariate space tend to deviate from the model in the same direction.
Goeman, Jelle J., Le Cessie, Saskia
openaire   +2 more sources

Special restrictions in multinomial logistic regression [PDF]

Stata Technical Bulletin, 2000
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Modelling of land-use change in Thailand using binary logistic regression and multinomial logistic regression

Arabian Journal of Geosciences, 2020
Suhaimee Buya, P. Tongkumchum, B. E. Owusu   +2 more
semanticscholar   +1 more source