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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ordinalgmifs: An R Package for Ordinal Regression in High-dimensional Data Settings [PDF]
Cancer Informatics, 2014 High-throughput genomic assays are performed using tissue samples with the goal of classifying the samples as normal < pre-malignant < malignant or by stage of cancer using a small set of molecular features.
Kellie J. Archer +5 more
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Moving Window Regression: A Novel Approach to Ordinal Regression [PDF]
Computer Vision and Pattern Recognition, 2022 A novel ordinal regression algorithm, called moving window regression (MWR), is proposed in this paper. First, we propose the notion of relative rank ($\rho$-rank), which is a new order representation scheme for input and reference instances.
Nyeong-Ho Shin +2 more
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Ord2Seq: Regarding Ordinal Regression as Label Sequence Prediction [PDF]
IEEE International Conference on Computer Vision, 2023 Ordinal regression refers to classifying object instances into ordinal categories. It has been widely studied in many scenarios, such as medical disease grading and movie rating.
Jin-Hong Wang +5 more
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Deep neural networks for rank-consistent ordinal regression based on conditional probabilities [PDF]
Pattern Analysis and Applications, 2021 In recent times, deep neural networks achieved outstanding predictive performance on various classification and pattern recognition tasks. However, many real-world prediction problems have ordinal response variables, and this ordering information is ...
Xintong Shi, Wenzhi Cao, S. Raschka
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OrdinalCLIP: Learning Rank Prompts for Language-Guided Ordinal Regression [PDF]
Neural Information Processing Systems, 2022 This paper presents a language-powered paradigm for ordinal regression. Existing methods usually treat each rank as a category and employ a set of weights to learn these concepts.
Wanhua Li +6 more
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Distributed Ordinal Regression Over Networks
IEEE Access, 2021 Many real-world data are labeled with natural orders, i.e., ordinal labels. Examples can be found in a wide variety of fields. Ordinal regression is a problem to predict ordinal labels for given patterns.
Huan Liu, Jiankai Tu, Chunguang Li
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ORDINAL LOGISTIC REGRESSION MODEL AND CLASSIFICATION TREE ON ORDINAL RESPONSE DATA
Barekeng, 2022 Logistic regression (LR) is a model that associates the relationship between category-type response variables with quantitative or quantitative and qualitative predictor variables. The prediction of the LR model is in the form of probability.
Jajang Jajang +2 more
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Unimodal-Concentrated Loss: Fully Adaptive Label Distribution Learning for Ordinal Regression [PDF]
Computer Vision and Pattern Recognition, 2022 Learning from a label distribution has achieved promising results on ordinal regression tasks such as facial age and head pose estimation wherein, the concept of adaptive label distribution learning (ALDL) has drawn lots of attention recently for its ...
Qiang Li +7 more
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Statistical Analysis of Ordinal Response Variable: A Comparative Study [PDF]
المجلة العراقية للعلوم الاحصائية, 2022 Response variables in biological phenomena vary between three types: numerical response variables, ordinal categorical response variables, and nominal categorical response variables. In statistical studies, handling ordinal variables varies in accordance
Liqaa Alhamdany, Zaid Tariq Salah
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