Results 1 to 10 of about 90,248 (307)
Robust Estimation and Filtering Methods for Ordinal Label Noise [PDF]
Jisuanji kexueLarge-scale labeled datasets inevitably contain label noise,which limits the generalization performance of the model to some extent.The labels of ordinal regression datasets are discrete values,but there exist ordinal relationships between different ...
JIANG Gaoxia, WANG Fei, XU Hang, WANG Wenjian
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Implementing Analysis of Ordinal Regression Model on Student’s Feedback Response
Cihan University-Erbil Journal of Humanities and Social Sciences, 2021 Instruction is a multidimensional procedure including a quantity of features, e.g., tutor qualities, that occasionally are hard to assess. In certain points, education efficiency, that is a part of instructing, is affected by a combination of teacher ...
Dler H. Kadir, Ameera W. Omer
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Sparse Ordinal Logistic Regression and Its Application to Brain Decoding
Frontiers in Neuroinformatics, 2018 Brain decoding with multivariate classification and regression has provided a powerful framework for characterizing information encoded in population neural activity.
Emi Satake +4 more
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Ordinal Regression Based Subpixel Shift Estimation for Video Super-Resolution
EURASIP Journal on Advances in Signal Processing, 2007 We present a supervised learning-based approach for subpixel motion estimation which is then used to perform video super-resolution. The novelty of this work is the formulation of the problem of subpixel motion estimation in a ranking framework.
Nemanja Petrovic +3 more
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mvord: An R Package for Fitting Multivariate Ordinal Regression Models
Journal of Statistical Software, 2020 The R package mvord implements composite likelihood estimation in the class of multivariate ordinal regression models with a multivariate probit and a multivariate logit link.
Rainer Hirk, Kurt Hornik, Laura Vana
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Penalized Regression with Ordinal Predictors [PDF]
International Statistical Review, 2009 SummaryOrdered categorial predictors are a common case in regression modelling. In contrast to the case of ordinal response variables, ordinal predictors have been largely neglected in the literature. In this paper, existing methods are reviewed and the use of penalized regression techniques is proposed.
Gertheiss, Jan, Tutz, Gerhard
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MANAS: Journal of Engineering, 2022 In cases where the dependent variable is categorical and ordinal, the Ordinal Logistic Regression Model is used for model estimation. In order to predict the Ordinal Logistic Regression Model, it must provide the parallel lines assumption.
Burak Uyar, Cevdet Büyüksu
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Asian Nursing Research, 2020 Summary: Purpose: The purpose of this study was to identify the factors affecting the satisfaction with patient-controlled analgesia (PCA) of patients using a generalized ordinal logistic regression model and to evaluate the difference in results of the
Wonhee Baek +3 more
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The Scientific World Journal, 2022 Background. Socioeconomic status (SES) refers to an individual’s or group’s social position or class, which is often determined by a combination of education, income, and occupation.
Mesfin Esayas Lelisho +2 more
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Prevalence and underlying factors of mobile game addiction among university students in Bangladesh
Cambridge Prisms: Global Mental Health, 2021 Background Nowadays, the youth are more engaging with their more advanced smartphones having high-quality graphics and gaming features. However, existing literature depicts that adolescents suffer from several forms of psychological problems including ...
Md Abu Sayeed +3 more
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