Results 41 to 50 of about 5,941,658 (334)
Prediction of the Fundus Tessellation Severity With Machine Learning Methods
Frontiers in Medicine, 2022 PurposeTo predict the fundus tessellation (FT) severity with machine learning methods.MethodsA population-based cross-sectional study with 3,468 individuals (mean age of 64.6 ± 9.8 years) based on Beijing Eye Study 2011.
Lei Shao +11 more
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Improving Deep Regression with Ordinal Entropy [PDF]
International Conference on Learning Representations, 2023 In computer vision, it is often observed that formulating regression problems as a classification task often yields better performance. We investigate this curious phenomenon and provide a derivation to show that classification, with the cross-entropy ...
Shi-Hao Zhang +4 more
semanticscholar +1 more source
Penalized Regression with Ordinal Predictors [PDF]
, 2008 Ordered categorial predictors are a common case in regression modeling. In contrast to the case of ordinal response variables, ordinal predictors have been largely neglected in the literature. In this article penalized regression techniques are proposed.
Gertheiss, Jan, Tutz, Gerhard
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Smoothing in Ordinal Regression: An Application to Sensory Data
Stats, 2021 The so-called proportional odds assumption is popular in cumulative, ordinal regression. In practice, however, such an assumption is sometimes too restrictive.
Ejike R. Ugba +2 more
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Proceedings of the 8th conference of the European Society for Fuzzy Logic and Technology, 2013 We propose an extension of choquistic regression from the case of binary to the case of ordinal classification. Choquistic regression itself has been introduced recently as a generalization of conventional logistic regression. The basic idea of this method is to replace the linear function of predictor variables in the logistic regression model by the ...
Tehrani, Ali Fallah, Hüllermeier, Eyke
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Ordinal Ridge Regression with Categorical Predictors [PDF]
, 2011 In multi-category response models categories are often ordered. In case of ordinal response models, the usual likelihood approach becomes unstable with ill-conditioned predictor space or when the number of parameters to be estimated is large relative to ...
Zahid, Faisal Maqbool
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Self-Trained Deep Ordinal Regression for End-to-End Video Anomaly Detection [PDF]
Computer Vision and Pattern Recognition, 2020 Video anomaly detection is of critical practical importance to a variety of real applications because it allows human attention to be focused on events that are likely to be of interest, in spite of an otherwise overwhelming volume of video. We show that
Guansong Pang +4 more
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Binary and Ordinal Random Effects Models Including Variable Selection [PDF]
, 2010 A likelihood-based boosting approach for fitting binary and ordinal mixed models is presented. In contrast to common procedures it can be used in high-dimensional settings where a large number of potentially influential explanatory variables is available.
Groll, Andreas, Tutz, Gerhard
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E-Jurnal Matematika, 2023 This research was conducted to determine the variables that have a significant impact on the stages of a well-off family in Sidemen Sub-district based on indicators obtained from the BKKBN and to classify the stages of a well-off family.
I GUSTI NGURAH SENTANA PUTRA +2 more
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Comput. Biol. Medicine, 2022 Although for many diseases there is a progressive diagnosis scale, automatic analysis of grade-based medical images is quite often addressed as a binary classification problem, missing the finer distinction and intrinsic relation between the different ...
Santiago Toledo-Cortés +3 more
semanticscholar +1 more source