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Ordinal regression for interaction quality prediction
2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014The automatic prediction of the quality of a dialogue is useful to keep track of a spoken dialogue system's performance and, if necessary, adapt its behaviour. Classifiers and regression models have been suggested to make this prediction. The parameters of these models are learnt from a corpus of dialogues evaluated by users or experts.
El Asri, Layla +3 more
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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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A Metric Approach for Ordinal Regression
1997This 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.
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Ordinal Regression with Sparse Bayesian
2009In this paper, a probabilistic framework for ordinal prediction is proposed, which can be used in modeling ordinal regression. A sparse Bayesian treatment for ordinal regression is given by us, in which an automatic relevance determination prior over weights is used. The inference techniques based on Laplace approximation is adopted for model selection.
Xiao Chang, Qinghua Zheng, Peng Lin
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Regression Models for Ordinal Outcomes
JAMA, 2022Benjamin, French, Matthew S, Shotwell
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Ordinal Regression in Evolutionary Computation
2006Surrogate 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.
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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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Relative margin induced support vector ordinal regression
Expert Systems With Applications, 2023Weidu Ye, , Fa Zhu
exaly