Results 21 to 30 of about 2,450,039 (300)
Ordinal Regression Model of Parking Search Time
Promet (Zagreb), 2023 Parking search reduces the quality of parking service, as well as traffic network level of service, due to additionally generated traffic. Parking search also entails other negative effects, primarily ecological, social and economic.
Jelena Simićević +2 more
doaj +1 more source
Statistical Analysis of Ordinal Response Variable: A Comparative Study [PDF]
المجلة العراقية للعلوم الاحصائية, 2022 Response variables in biological phenomena vary between three types: numerical response variables, ordinal categorical response variables, and nominal categorical response variables. In statistical studies, handling ordinal variables varies in accordance
Liqaa Alhamdany, Zaid Tariq Salah
doaj +1 more source
Jambura Journal of Mathematics, 2023 Diabetes is one of the high-risk diseases. The most prominent symptom of this disease is high blood sugar levels. People with diabetes in Indonesia can reach 30 million people.
Assyifa Lala Pratiwi Hamid +4 more
doaj +1 more source
Active Learning for Imbalanced Ordinal Regression
IEEE Access, 2020 Ordinal regression (OR), also called ordinal classification, is a special multi-classification designed for problems with ordered classes. Imbalanced data hinders the performance of classification algorithms, especially for OR algorithms, as imbalanced ...
Jiaming Ge +4 more
doaj +1 more source
Pairwise Fairness for Ordinal Regression
CoRR, 2021 We initiate the study of fairness for ordinal regression. We adapt two fairness notions previously considered in fair ranking and propose a strategy for training a predictor that is approximately fair according to either notion. Our predictor has the form of a threshold model, composed of a scoring function and a set of thresholds, and our strategy is ...
Kleindessner, M. +4 more
openaire +5 more sources
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
doaj +1 more source
Convolutional Ordinal Regression Forest for Image Ordinal Estimation [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2022 Image ordinal estimation is to predict the ordinal label of a given image, which can be categorized as an ordinal regression problem. Recent methods formulate an ordinal regression problem as a series of binary classification problems. Such methods cannot ensure that the global ordinal relationship is preserved since the relationships among different ...
Haiping Zhu +7 more
openaire +4 more sources
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
doaj +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
core +1 more source
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
openaire +2 more sources