Results 251 to 260 of about 109,915 (302)
JCPP Advances, EarlyView.Abstract Background Excess weight and weight concern among adolescents can lead to adverse physical and psychosocial health consequences. This study aims to examine levels of weight concern, desire for weight support, and their associations in adolescents.
Melissa Little +5 more
wiley +1 more source
A two-wave longitudinal panel dataset on United States public acceptance of Precision Livestock Farming technology in swine production. [PDF]
Data BriefAkinyemi BE, Siegford JM.
europepmc +1 more source
Automatic Grade Classification in Prostate Histopathological Images Using EfficientNet and Ordinal Focal Loss. [PDF]
Bioengineering (Basel)Rodrigues WVS +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 OneWondie KY +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
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 +3 more
openaire +2 more sources
Ordinal regression based on learning vector quantization [PDF]
Neural Networks, 2017 Recently, ordinal regression, which predicts categories of ordinal scale, has received considerable attention. In this paper, we propose a new approach to solve ordinal regression problems within the learning vector quantization framework. It extends the
Fengzhen Tang, Peter Tino
exaly +3 more sources
Kernel Discriminant Learning for Ordinal Regression
IEEE Transactions on Knowledge and Data Engineering, 2010 Ordinal regression has wide applications in many domains where the human evaluation plays a major role. Most current ordinal regression methods are based on Support Vector Machines (SVM) and suffer from the problems of ignoring the global information of ...
Jiuyong Li, Desheng Wu, Wen-Bo Li
exaly +2 more sources
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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 +3 more
openaire +1 more source
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 +3 more
openaire +1 more source