Results 11 to 20 of about 87,051 (257)
Distributed Ordinal Regression Over Networks [PDF]
Many real-world data are labeled with natural orders, i.e., ordinal labels. Examples can be found in a wide variety of fields. Ordinal regression is a problem to predict ordinal labels for given patterns.
Huan Liu, Jiankai Tu, Chunguang Li
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Regularized Ordinal Regression and the ordinalNet R Package. [PDF]
Regularization techniques such as the lasso (Tibshirani 1996) and elastic net (Zou and Hastie 2005) can be used to improve regression model coefficient estimation and prediction accuracy, as well as to perform variable selection.
Wurm MJ, Rathouz PJ, Hanlon BM.
europepmc +2 more sources
Ordinal regression increases statistical power to predict epilepsy surgical outcomes. [PDF]
Studies of epilepsy surgery outcomes are often small and thus underpowered to reach statistically valid conclusions. We hypothesized that ordinal logistic regression would have greater statistical power than binary logistic regression when analyzing ...
Dickey AS, Krafty RT, Pedersen NP.
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ORDINAL LOGISTIC REGRESSION MODEL AND CLASSIFICATION TREE ON ORDINAL RESPONSE DATA
Logistic regression (LR) is a model that associates the relationship between category-type response variables with quantitative or quantitative and qualitative predictor variables. The prediction of the LR model is in the form of probability.
Jajang Jajang +2 more
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Statistical Analysis of Ordinal Response Variable: A Comparative Study [PDF]
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
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Ordinal Regression Model of Parking Search Time
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
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Predicting progression of Alzheimer's disease using ordinal regression. [PDF]
We propose a novel approach to predicting disease progression in Alzheimer's disease (AD)--multivariate ordinal regression--which inherently models the ordered nature of brain atrophy spanning normal aging (CTL) to mild cognitive impairment (MCI) to AD ...
Doyle OM +10 more
europepmc +2 more sources
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
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Active Learning for Imbalanced Ordinal Regression
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
ENSEMBLE BAGGING WITH ORDINAL LOGISTIC REGRESSION TO CLASSIFY TODDLER NUTRITIONAL STATUS
One problem in classifying stunting data is that the data used does not have a balanced proportion. This study aims to apply the logistic regression classification method with ordinal scale response variables to overcome class imbalance through the ...
Luthfia Hanun Yuli Arini +3 more
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