Results 51 to 60 of about 2,450,039 (300)
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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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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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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Rank regression for analyzing ordinal qualitative data for treatment comparison [PDF]
, 2012 Ordinal qualitative data are often collected for phenotypical measurements in plant pathology and other biological sciences. Statistical methods, such as t tests or analysis of variance, are usually used to analyze ordinal data when comparing two groups ...
Wang, Y. -G. +3 more
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STATISTICAL RANK METHODS FOR ORDINAL CATEGORICAL DATA [PDF]
, 1991 The aim of this paper is to present a new rank. method for analysing ordinal scale problems, and to give some of its basic properties. The method is suitable for the assessment of validity and reliability of health measurement instruments.
Holm, Sture, Svensson, Elisabeth
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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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Qualitative ordinal scales: the concept of ordinal range [PDF]
, 2004 Many practical problems of quality control involve the use of ordinal scales. Questionnaires planned to collect judgments on qualitative or linguistic scales, whose levels are terms such as "good," "bad," "medium," etc., are extensively used both in ...
Franceschini, Fiorenzo +6 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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