Results 21 to 30 of about 90,248 (307)

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, Nataša Vidović, Vladimir Đorić   +2 more
doaj   +1 more source

Transductive Ordinal Regression [PDF]

IEEE Transactions on Neural Networks and Learning Systems, 2012
Ordinal regression is commonly formulated as a multi-class problem with ordinal constraints. The challenge of designing accurate classifiers for ordinal regression generally increases with the number of classes involved, due to the large number of labeled patterns that are needed.
Seah, Chun-Wei, Tsang, Ivor Wai-Hung, Ong, Yew Soon   +2 more
openaire   +4 more sources

The Comparison between Ordinal Logistic Regression and Random Forest Ordinal in Identifying the Factors Causing Diabetes Mellitus

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, Anwar Fitrianto, Indahwati Indahwati, Erfiani Erfiani, Khusnia Nurul Khikmah   +4 more
doaj   +1 more source

Support Vector Ordinal Regression [PDF]

Neural Computation, 2007
In this letter, we propose two new support vector approaches for ordinal regression, which optimize multiple thresholds to define parallel discriminant hyperplanes for the ordinal scales. Both approaches guarantee that the thresholds are properly ordered at the optimal solution.
Chu, Wei, Keerthi, S. Sathiya
openaire   +2 more sources

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, Haiyan Chen, Dongfang Zhang, Xiaye Hou, Ligang Yuan   +4 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, Hongming Shan, Yuheng Zhang, Lingfu Che, Xiaoyang Xu, Junping Zhang, Jianbo Shi, Fei-Yue Wang   +7 more
openaire   +3 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, Xiaomei Zhang, Teng Hu, Yang Chen, Chuan Zhang, Li Dong, Saiguang Ling, Zhou Dong, Wen Da Zhou, Rui Heng Zhang, Lei Qin, Wen Bin Wei   +11 more
doaj   +1 more source

KLASIFIKASI TINGKAT KESEJAHTERAAN KELUARGA DI KECAMATAN SIDEMEN MENGGUNAKAN BOOTSTRAP AGGREGATING (BAGGING) REGRESI LOGISTIK ORDINAL

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, MADE SUSILAWATI, I PUTU WINADA GAUTAMA   +2 more
doaj   +1 more source

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, Daniel Mörlein, Jan Gertheiss   +2 more
doaj   +1 more source

Ordinal Choquistic Regression

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 ...
Eyke Huellermeier, Ali Fallah Tehrani
openaire   +3 more sources