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Neighborhood preserving ordinal regression
Proceedings of the 4th International Conference on Internet Multimedia Computing and Service, 2012Ordinal regression, which aims at determining the rating of a data item on a discrete rating scale, is an important research topic in pattern mining and multimedia data analysis. Most of the existing approaches of ordinal regression try to seek only one direction on which the projected data are well ranked.
Yang Liu +3 more
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Group truncated ordinal regression
Statistics & Probability Letters, 1995zbMATH Open Web Interface contents unavailable due to conflicting licenses.
O'Neill, Terence J., Barry, Simon C.
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2001
Many medical and epidemiologic studies incorporate an ordinal response variable. In some cases an ordinal response Y represents levels of a standard measurement scale such as severity of pain (none, mild, moderate, severe). In other cases, ordinal responses are constructed by specifying a hierarchy of separate endpoints.
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Many medical and epidemiologic studies incorporate an ordinal response variable. In some cases an ordinal response Y represents levels of a standard measurement scale such as severity of pain (none, mild, moderate, severe). In other cases, ordinal responses are constructed by specifying a hierarchy of separate endpoints.
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ORDINAL REGRESSION MODELS FOR EPIDEMIOLOGIC DATA
American Journal of Epidemiology, 1989Health status is often measured in epidemiologic studies on an ordinal scale, but data of this type are generally reduced for analysis to a single dichotomy. Several statistical models have been developed to make full use of information in ordinal response data, but have not been much used in analyzing epidemiologic studies.
B G, Armstrong, M, Sloan
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Ordinal Regression With Pinball Loss
IEEE Transactions on Neural Networks and Learning SystemsOrdinal regression (OR) aims to solve multiclass classification problems with ordinal classes. Support vector OR (SVOR) is a typical OR algorithm and has been extensively used in OR problems. In this article, based on the characteristics of OR problems, we propose a novel pinball loss function and present an SVOR method with pinball loss (pin-SVOR ...
Guangzheng Zhong +4 more
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Ordinal Regression and Ranking
2011Accurate ordering or ranking over instances is of paramount importance for several applications (Faria et al. Learning to rank for content-based image retrieval. In: Proceedings of the Multimedia Information Retrieval Conference, pp. 285–294, 2010; Veloso et al. Learning to rank at query-time using association rules.
Adriano Veloso, Wagner Meira
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Bayesian Hierarchical Ordinal Regression
2005We present a Bayesian approach to ordinal regression. Our model is based on a hierarchical mixture of experts model and performs a soft partitioning of the input space into different ranks, such that the order of the ranks is preserved. Experimental results on benchmark data sets show a comparable performance to support vector machine and Gaussian ...
Ulrich Paquet +2 more
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Alternative models for ordinal logistic regression
Statistics in Medicine, 1994AbstractArmstrong and Sloan have reviewed two types of ordinal logistic models for epidemiologic data: the cumulative‐odds model and the continuation‐ratio model. I review here certain aspects of these models not emphasized previously, and describe a third type, the stereotype model, which in certain situations offers greater flexibility coupled with ...
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Regression Models for Ordinal Outcomes
JAMA, 2022Benjamin, French, Matthew S, Shotwell
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