Results 51 to 60 of about 2,609,891 (296)
Ordinal Regression as Structured Classification
CoRR, 2019 This paper extends the class of ordinal regression models with a structured interpretation of the problem by applying a novel treatment of encoded labels. The net effect of this is to transform the underlying problem from an ordinal regression task to a (structured) classification task which we solve with conditional random fields, thereby achieving a ...
Niall Twomey +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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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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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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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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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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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
wiley +1 more source
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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Estimates of the ordinal logistic regression model.
, 2022 Estimates of the ordinal logistic regression model.
Daniela Costa (830554) +3 more
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