Results 31 to 40 of about 90,248 (307)
Geographically Weighted Probit Ordinal Regression Model Estimation [PDF]
E3S Web of ConferencesGeographically 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 +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 +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 +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
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 +2 more
doaj +1 more source
Incremental sparse Bayesian ordinal regression
Neural Networks, 2018 Ordinal Regression (OR) aims to model the ordering information between different data categories, which is a crucial topic in multi-label learning. An important class of approaches to OR models the problem as a linear combination of basis functions that map features to a high dimensional non-linear space.
Chang Li, Maarten de Rijke
openaire +6 more sources
Dwell Time Estimation of Import Containers as an Ordinal Regression Problem
Applied Sciences, 2021 The optimal stacking of import containers in a terminal reduces the reshuffles during the unloading operations. Knowing the departure date of each container is critical for optimal stacking.
Laidy De Armas Jacomino +5 more
doaj +1 more source
E-Jurnal Matematika, 2016 This research was conducted to determine the variables that significantly influence nutritional status of children based on indicators that defined as height for age (H/A) and to classify children nutritional status into normal, short or very short ...
PALUPI PURNAMA SARI +2 more
doaj +1 more source