Results 11 to 20 of about 4,818,434 (320)
LASSO and Elastic Net Tend to Over-Select Features
Mathematics, 2023 Machine learning methods have been a standard approach to select features that are associated with an outcome and to build a prediction model when the number of candidate features is large. LASSO is one of the most popular approaches to this end.
Lu Liu +3 more
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A Robust Variable Selection Method for Sparse Online Regression via the Elastic Net Penalty
Mathematics, 2022 Variable selection has been a hot topic, with various popular methods including lasso, SCAD, and elastic net. These penalized regression algorithms remain sensitive to noisy data.
Wentao Wang +4 more
doaj +2 more sources
Mathematics, 2021 The lasso and elastic net methods are the popular technique for parameter estimation and variable selection. Moreover, the adaptive lasso and elastic net methods use the adaptive weights on the penalty function based on the lasso and elastic net ...
Autcha Araveeporn
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An elastic net orthogonal forward regression algorithm [PDF]
IFAC Proceedings Volumes, 2012 In this paper we propose an efficient two-level model identification method for a large class of linear-in-the-parameters models from the observational data. A new elastic net orthogonal forward regression (ENOFR) algorithm is employed at the lower level
Chen, Sheng, Hong, Xia
core +3 more sources
Improved Metabolite Prediction Using Microbiome Data-Based Elastic Net Models [PDF]
Frontiers in Cellular and Infection Microbiology, 2021 Microbiome data are becoming increasingly available in large health cohorts, yet metabolomics data are still scant. While many studies generate microbiome data, they lack matched metabolomics data or have considerable missing proportions of metabolites ...
Jialiu Xie +12 more
doaj +2 more sources
Adaptive group-regularized logistic elastic net regression. [PDF]
Biostatistics, 2021 SummaryIn high-dimensional data settings, additional information on the features is often available. Examples of such external information in omics research are: (i) $p$-values from a previous study and (ii) omics annotation. The inclusion of this information in the analysis may enhance classification performance and feature selection but is not ...
Münch MM +3 more
europepmc +6 more sources
Sparse HJ Biplot: A New Methodology via Elastic Net
Mathematics, 2021 The HJ biplot is a multivariate analysis technique that allows us to represent both individuals and variables in a space of reduced dimensions. To adapt this approach to massive datasets, it is necessary to implement new techniques that are capable of ...
Mitzi Cubilla-Montilla +3 more
doaj +2 more sources
A Cluster Elastic Net for Multivariate Regression [PDF]
, 2018 We propose a method for estimating coefficients in multivariate regression when there is a clustering structure to the response variables. The proposed method includes a fusion penalty, to shrink the difference in fitted values from responses in the same
Price, Bradley S., Sherwood, Ben
core +4 more sources
Communications in Statistics: Case Studies, Data Analysis and Applications, 2023 A new penalized likelihood method (reciprocal elastic net) is put forward for regularization and variable selection. Our proposal is based on a new class of reciprocal penalty functions, combining the strengths of the reciprocal LASSO regularization and ...
Rahim Alhamzawi +2 more
openaire +2 more sources
Exploring influencing factors of chronic obstructive pulmonary disease based on elastic net and Bayesian network. [PDF]
Sci Rep, 2022 This study aimed to construct Bayesian networks (BNs) to analyze the network relationships between COPD and its influencing factors, and the strength of each factor's influence on COPD was reflected through network reasoning. Elastic Net and Max-Min Hill-
Quan D +8 more
europepmc +2 more sources