Results 51 to 60 of about 2,640,523 (250)
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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Assumptions of ordinal logistic regression (N = 530).
, 2022 Assumptions of ordinal logistic regression (N = 530).
Zewdie Birhanu (364608) +5 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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Ordinal regression increases statistical power to predict epilepsy surgical outcomes
Epilepsia Open, 2022 Studies of epilepsy surgery outcomes are often small and thus underpowered to reach statistically valid conclusions. We hypothesized that ordinal logistic regression would have greater statistical power than binary logistic regression when analyzing ...
Adam S. Dickey +2 more
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Multiclass ordinal modeling of diabetes risk using bivariate polynomial ordinal logistic regression
Social Sciences and Humanities OpenThis study provides an empirical validation and diagnostic evaluation of the Bivariate Polynomial Ordinal Logistic Regression (BPOLR) model for simultaneously modeling two correlated ordinal response variables with nonlinear predictors.
Wisnowan Hendy Saputra +3 more
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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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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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A constrained regression model for an ordinal response with ordinal predictors [PDF]
Statistics and Computing, 2018 A regression model is proposed for the analysis of an ordinal response variable depending on a set of multiple covariates containing ordinal and potentially other variables. The proportional odds model (McCullagh (1980)) is used for the ordinal response, and constrained maximum likelihood estimation is used to account for the ordinality of covariates ...
Espinosa, Javier, Hennig, Christian
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Adult survivors of childhood acute lymphoblastic leukemia (ALL) are at risk of reduced exercise capacity, decreased physical activity levels, persistent fatigue, and neurocognitive deficits. The aim was to investigate exercise capacity and physical activity levels of adult survivors of childhood ALL and their associations with ...
Laura Jess +5 more
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Regression to Classification: Ordinal Prediction of Calcified Vessels Using Customized ResNet50
IEEE Access, 2023 A substantial percentage of women die from cardiovascular disease (CVD). Computed tomography (CT) scan helps predict/monitor CVD-related diseases. However, previous studies found relation to assessing the risk of CVD by estimating severity of breast ...
Hosna Asma-Ull, Il Dong Yun, Bo La Yun
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