Results 261 to 270 of about 2,609,891 (296)

Bayesian Hierarchical Ordinal Regression

2005
We 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, Sean B. Holden, Andrew Naish-Guzman   +2 more
openaire   +1 more source

A Metric Approach for Ordinal Regression

1997
This paper presents a metric approach for the regression of ordinal variables. In contrast to most other studies, the problem of independent, ordinal variables with a dependent variable that is a metric scale is analyzed. For this situation, some properties of the estimated parameters of the model are described.
openaire   +1 more source

Ordinal Regression in Evolutionary Computation

2006
Surrogate ranking in evolutionary computation using ordinal regression is introduced. The fitness of individual points is indirectly estimated by modeling their rank. The aim is to reduce the number of costly fitness evaluations needed for evolution.
openaire   +2 more sources

Companion Losses for Ordinal Regression

2022
David Díaz-Vico, Ángela Fernández 0001, José R. Dorronsoro   +2 more
openaire   +2 more sources

Ordinal Regression and Ranking

2011
Accurate 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
openaire   +1 more source

Regression Models for Ordinal Outcomes

JAMA, 2022
Benjamin, French, Matthew S, Shotwell
openaire   +2 more sources

Relative margin induced support vector ordinal regression

Expert Systems With Applications, 2023
Weidu Ye, Fa Zhu
exaly  

Non-parallel hyperplanes ordinal regression machine

Knowledge-Based Systems, 2021
Zhixia Yang
exaly  

Ordinal Logistic Regression With Partial Proportional Odds for Depression Prediction

IEEE Transactions on Affective Computing, 2023
Sadari Jayawardena, Julien Epps, Eliathamby Ambikairajah   +2 more
exaly  

Deep and interpretable regression models for ordinal outcomes

Pattern Recognition, 2022
Torsten Hothorn, Beate Sick, Lucas Kook
exaly