Results 31 to 40 of about 109,915 (302)

Evaluation Measures for Ordinal Regression

open access: yes2009 Ninth International Conference on Intelligent Systems Design and Applications, 2009
Ordinal regression (OR -- also known as ordinal classification) has received increasing attention in recent times, due to its importance in IR applications such as learning to rank and product review rating. However, research has not paid attention to the fact that typical applications of OR often involve datasets that are highly imbalanced.
Baccianella S, Esuli A, Sebastiani F
openaire   +3 more sources

Minimum enclosing spheres formulations for support vector ordinal regression [PDF]

open access: yes, 2006
We present two new support vector approaches for ordinal regression. These approaches find the concentric spheres with minimum volume that contain most of the training samples.
S.K. Shevade   +3 more
core   +1 more source

Regression with Ordered Predictors via Ordinal Smoothing Splines

open access: yesFrontiers 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

open access: yesRevista 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

Dwell Time Estimation of Import Containers as an Ordinal Regression Problem

open access: yesApplied 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

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

open access: yesJournal 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

Feature selection for ordinal regression [PDF]

open access: yesProceedings of the 2010 ACM Symposium on Applied Computing, 2010
Ordinal classification (also known as ordinal regression) is a supervised learning task that consists of automatically determining the implied rating of a data item on a fixed, discrete rating scale. This problem is receiving increasing attention from the sentiment analysis and opinion mining community, due to the importance of automatically rating ...
Baccianella S, Esuli A, Sebastiani F
openaire   +2 more sources

BOOTSTRAP AGGREGATING (BAGGING) REGRESI LOGISTIK ORDINAL UNTUK MENGKLASIFIKASIKAN STATUS GIZI BALITA DI KABUPATEN KLUNGKUNG

open access: yesE-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

On the Consistency of Ordinal Regression Methods

open access: yesJ. Mach. Learn. Res., 2014
Many of the ordinal regression models that have been proposed in the literature can be seen as methods that minimize a convex surrogate of the zero-one, absolute, or squared loss functions. A key property that allows to study the statistical implications of such approximations is that of Fisher consistency.
Pedregosa, Fabian   +2 more
openaire   +4 more sources

Sparse Ordinal Logistic Regression and Its Application to Brain Decoding

open access: yesFrontiers in Neuroinformatics, 2018
Brain decoding with multivariate classification and regression has provided a powerful framework for characterizing information encoded in population neural activity.
Emi Satake   +4 more
doaj   +1 more source

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