Results 21 to 30 of about 87,051 (257)

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

Geographically Weighted Probit Ordinal Regression Model Estimation [PDF]

E3S Web of Conferences
Geographically Weighted Probit Ordinal Regression (GWPOR) is a combined method between Geographically Weighted Regression and Probit Ordinal Regression. This study estimates the percentage of poor people using the GWPOR method.
Kurniawan Muh. Idham, Purhadi, Rahayu Santi Puteri   +2 more
doaj   +1 more source

Twitter Sentiment Analysis Based on Ordinal Regression

IEEE Access, 2019
In recent years, research on Twitter sentiment analysis, which analyzes Twitter data (tweets) to extract user sentiments about a topic, has grown rapidly. Many researchers prefer the use of machine learning algorithms for such analysis.
Shihab Elbagir Saad, Jing Yang
doaj   +1 more source

Predictive Factors for Pelvic Organ Prolapse (POP) in Iranian Women’s: An Ordinal Logistic Approch [PDF]

Journal of Clinical and Diagnostic Research, 2014
Introduction: To investigate the predictors factors of Pelvic Organ Prolapse (POP) in Iranian women by using ordinal logistic regression. Materials and Methods: The role of risk factors of POP was evaluated among 365 patients attending in two public ...
Ashraf Direkvand-Moghadam, Zeinab Ghazanfari, Kourosh Sayehmiri   +2 more
doaj   +1 more source

Ordinal regression model for pea seed mass

Die Bodenkultur, 2017
The development of seeds at various positions in the pod is asynchronous. Thus, the differences of seed dry mass production because of environmental conditions may depend on the cultivar type, type of inoculants and interrelations between seeds per pod ...
Klimek-Kopyra Agnieszka, Strojny Jacek, Zając Tadeusz, Ślizowska Anna, Klimešova Jana, Neugschwandtner Reinhard W.   +5 more
doaj   +1 more source

Simultaneous optimization of quantitative and ordinal responses using Taguchi method [PDF]

International Journal of Research in Industrial Engineering, 2018
In the real world, the overall quality of a product is often represented partly by the measured values of some quantitative variables and partly by the observed values of some ordinal variables.
S. Pal, S. Gauri
doaj   +1 more source

Regression with Ordered Predictors via Ordinal Smoothing Splines

Frontiers in Applied Mathematics and Statistics, 2017
Many applied studies collect one or more ordered categorical predictors, which do not fit neatly within classic regression frameworks. In most cases, ordinal predictors are treated as either nominal (unordered) variables or metric (continuous) variables ...
Nathaniel E. Helwig, Nathaniel E. Helwig
doaj   +1 more source

Regressão logística ordinal em estudos epidemiológicos Regresión logística ordinal en estudios epidemiológicos Ordinal logistic regression in epidemiological studies

Revista de Saúde Pública, 2009
Os modelos de regressão logística ordinal vêm sendo aplicados com sucesso na análise de estudos epidemiológicos. Entretanto, a verificação da adequação de cada modelo tem recebido atenção limitada.
Mery Natali Silva Abreu, Arminda Lucia Siqueira, Waleska Teixeira Caiaffa   +2 more
doaj   +1 more source