Distributed Support Vector Ordinal Regression over Networks [PDF]
Ordinal regression methods are widely used to predict the ordered labels of data, among which support vector ordinal regression (SVOR) methods are popular because of their good generalization.
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.
Michael J. Wurm +2 more
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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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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 ...
Adam S. Dickey +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 ...
Orla M Doyle +10 more
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An application of ordinal regression to extract social dysfunction levels through behavioral problems. [PDF]
Sabharwal A, Goyal B, Joshi LM.
europepmc +2 more sources
The Evaluation of Ordinal Regression Model's Performance Through the Implementation of Multilayer Feed-Forward Neural Network: A Case Study of Hypertension. [PDF]
Adnan MN +7 more
europepmc +3 more sources
Protein-protein interaction prediction based on ordinal regression and recurrent convolutional neural networks. [PDF]
Xu W, Gao Y, Wang Y, Guan J.
europepmc +3 more sources
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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