Elastic Net
Automated Variable Selection of Gamma-Ray Spectra by Utilization of LASSO and Elastic Net Techniques for Use in Nuclear Security Applications.
... Before diving into the detailed derivation for coordinate descent solutions to LASSO and Elastic Net, some background information and notations are necessary (Gauraha, 2018). Consider the standard linear ...
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Fully Adaptive Elastic-Net (Faelastic) For Gene Selection In High Dimensional Cancer Classification
... Abstract: Classification of cancer in high dimensional DNA microarray data establish a significant field of research. Though, because of the challenges face by higher dimensional data in selection of genes and ...
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Improving the Lexical Function Composition Model with Pathwise Optimized Elastic Net Regression
... introduced elastic- net regularized linear regression method, which is solved by the pathwise coordinate descent opti- mization algorithm along a regularization parame- ter ...the elastic-net ...
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Elastic net regularization approaches for genome wide association studies of rheumatoid arthritis
... the elastic-net regularization-based approach [5] to take the overall correlation structure of single-nucleo- tide polymorphisms (SNPs) into account when selecting disease-causing genes automatically in ...
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Application of Sparse Linear Discriminant Analysis and Elastic Net for Diagnosis of IgA Nephropathy: Statistical and Biological Viewpoints
... the dominant or co-dominant deposition of IgA in the glomerular mesangium that is usually accompanied by mesangial cellular proliferation and expansion of the ECM [33] . Although renal biopsy involves a risk of morbidity ...
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High Dimensional Logistic Regression Model using Adjusted Elastic Net Penalty
... the elastic net penalty which is based on a combined penalty of LASSO and ridge regression penalties in order to overcome the drawbacks of using the LASSO and ridge regression on their ...
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Ordinal Outcome Modeling: The Application of the Adaptive Moment Estimation Optimizer to the Elastic Net Penalized Stereotype Logit
... Penalized ordinal outcome models were developed to model high dimension- al data with ordinal outcomes. One option is the penalized stereotype logit, which includes nonlinear combinations of parameter estimates. ...
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Genomic selection using regularized linear regression models: ridge regression, lasso, elastic net and their extensions
... the elastic net and lasso performed better than ridge regres- sion, ridge regression BLUP and the adaptive extensions of lasso and the elastic ...the elastic net often outperforms RR ...
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Penalized Poisson Regression Model Using Elastic Net and Least Absolute Shrinkage and Selection Operator (Lasso) Penality
... The elastic net estimator for Poisson regression model is elastic net estimator is depended on non-negative two tuning parameters $ , $ ' and leads to penalized Poisson regression ...
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Geographically weighted elastic net logistic regression
... The elastic net (Zou and Hastie 2005) is a hybrid of ridge regression and lasso ...lasso, elastic net can result in model reduction by generating zero-valued coefficients so that the ...
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A Generalized Elastic Net Regularization with Smoothed l0 Penalty
... Abstract This paper presents an accurate and efficient algorithm for solving the generalized elastic net regularization problem with smoothed 0 penalty for recovering sparse vector.. F[r] ...
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Mutual kernelized correlation filters with elastic net constraint for visual tracking
... ENC: Elastic net constraint; FFT: Fast Fourier transform; FM: Fast motion; HOG: Histogram of oriented gradient; IPR: In-plane rotation; IV: Illumination variation; KCF: Kernelized correlation filters; ...
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Identifying the most informative features using a structurally interacting elastic net
... Feature selection can efficiently identify the most informative features with respect to the target feature used in training. However, state-of-the-art vector-based methods are unable to encapsulate the relationships ...
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A Cluster Elastic Net for Multivariate Regression
... The estimates of the re- gression coefficients and clusters are found by using a penalized likelihood estimator, which includes a cluster fusion penalty, to shrink the difference in fitt[r] ...
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A multi-tissue age prediction model based on DNA methylation analysis
... using elastic net regression, it was possible to identify 10 age-related (AR) DNA methylation markers across 41 samples coming from five types of tissue (whole blood, saliva, semen, menstrual blood, and ...
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PubMedCentral-PMC5830184.pdf
... the Elastic net method acquires better estimation and prediction than Lasso, ridge regression and adaptive Lasso methods by using a linear combination of l 1 and ridge ...However, Elastic net, ...
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Evaluating Common Strategies for the Efficiency of Feature Selection in the Context of Microarray Analysis
... These algorithms were chosen because they are commonly used in the litera- ture [8] and they are considered substantially different from each other. SGT is used extensively by itself or in combination with other ...
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Accurate ethnicity prediction from placental DNA methylation data
... an elastic net penalty (GLMNET) [37, 38], nearest shrunken centroids (NSC) [35, 69], K-nearest neighbours (KNN) [39], and support vector machines (SVM) ...
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Screening PubMed abstracts: is class imbalance always a challenge to machine learning?
... and elastic-net regularized generalized linear models) in combination with four techniques for class imbalance: random undersampling and oversampling with 50:50 and 35:65 positive to negative class ratios ...
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Combining anatomical, diffusion, and resting state functional magnetic resonance imaging for individual classification of mild and moderate Alzheimer's disease
... an elastic net classifier based on several measures de- rived from the MRI scans of mild to moderate AD patients (N=77) from the prospective registry on dementia study and controls (N=173) from the Austrian ...
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