Results 111 to 120 of about 96,053 (159)

Automatic Grade Classification in Prostate Histopathological Images Using EfficientNet and Ordinal Focal Loss. [PDF]

Bioengineering (Basel)
Rodrigues WVS, Luz A, Lima Araújo JD, Diniz J, Filho AO.   +4 more
europepmc   +1 more source

Content-qualified antenatal care coverage in Lesotho: An ordinal logistic regression analysis of the 2023-2024 demographic and health survey. [PDF]

PLoS One
Wondie KY, Tsega NT, Anteneh TA, Kassie AT, Mengistie BA, Wondifraw EB, Aragaw GM.   +6 more
europepmc   +1 more source

Physicians' Attitudes Toward Euthanasia in Türkiye: A Cross-Sectional Survey of Ethical Heterogeneity and Decision-Making Patterns. [PDF]

Healthcare (Basel)
Aydogan HC, Arslan HG, Yaşar Teke H.
europepmc   +1 more source

Ordinal Regression Models

, 2015
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Collaborative ordinal regression

Proceedings of the 23rd international conference on Machine learning - ICML '06, 2006
Ordinal regression has become an effective way of learning user preferences, but most research focuses on single regression problems. In this paper we introduce collaborative ordinal regression, where multiple ordinal regression tasks are handled simultaneously.
Shipeng Yu, Kai Yu 0001, Volker Tresp, Hans-Peter Kriegel   +3 more
openaire   +1 more source

Robust Ordinal Regression

2010
Within disaggregation–aggregation approach, ordinal regression aims at inducing parameters of a preference model, for example, parameters of a value function, which represent some holistic preference comparisons of alternatives given by the Decision Maker (DM).
Greco, Salvatore, Słowiński, Roman, Figueira, José Rui, Mousseau, Vincent   +3 more
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Multiple-Instance Ordinal Regression

IEEE Transactions on Neural Networks and Learning Systems, 2018
Ordinal regression (OR) is a paradigm in supervised learning, which aims at learning a prediction model for ordered classes. The existing studies mainly focus on single-instance OR, and the multi-instance OR problem has not been explicitly addressed. In many real-world applications, considering the OR problem from a multiple-instance aspect can yield ...
Yanshan Xiao, Bo Liu 0002, Zhifeng Hao
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Neighborhood preserving ordinal regression

Proceedings of the 4th International Conference on Internet Multimedia Computing and Service, 2012
Ordinal 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 0007, Yan Liu 0004, Keith C. C. Chan, Jing Zhang 0010   +3 more
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Soft Labels for Ordinal Regression

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Ordinal regression attempts to solve classification problems in which categories are not independent, but rather follow a natural order. It is crucial to classify each class correctly while learning adequate interclass ordinal relationships. We present a simple and effective method that constrains these relationships among categories by seamlessly ...
Raul Diaz, Amit Marathe
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Ordinal Regression With Pinball Loss

IEEE Transactions on Neural Networks and Learning Systems
Ordinal 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, Yanshan Xiao, Bo Liu 0002, Liang Zhao, Xiangjun Kong   +4 more
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