Results 41 to 50 of about 4,818,434 (320)
Journal of Applied Economics and Business Studies, 2021 This study aims at performance evaluation of Ridge, Elastic Net and Lasso Regression Methods in handling different degrees of multicollinearity in a multiple regression analysis of independent variables using simulation data.
Shady I. Altelbany
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Elastic-net regularization in learning theory
Journal of Complexity, 2009 Within the framework of statistical learning theory we analyze in detail the so-called elastic-net regularization scheme proposed by Zou and Hastie for the selection of groups of correlated variables. To investigate on the statistical properties of this scheme and in particular on its consistency properties, we set up a suitable mathematical framework.
C. DE MOL +2 more
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Adaptive Elastic Net for Group Testing
Biometrics, 2018 AbstractFor disease screening, group (pooled) testing can be a cost-saving alternative to one-at-a-time testing, with savings realized through assaying pooled biospecimen (eg, urine, blood, saliva). In many group testing settings, practitioners are faced with the task of conducting disease surveillance.
Karl B. Gregory +2 more
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Penalized Regression with Correlation Based Penalty [PDF]
, 2006 A new regularization method for regression models is proposed. The criterion to be minimized contains a penalty term which explicitly links strength of penalization to the correlation between predictors.
Tutz, Gerhard, Ulbricht, Jan
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Structure Adaptive Elastic-Net
, 2020 Penalized linear regression is of fundamental importance in high-dimensional statistics and has been routinely used to regress a response on a high-dimensional set of predictors. In many scientific applications, there exists external information that encodes the predictive power and sparsity structure of the predictors.
Pramanik, Sandipan, Zhang, Xianyang
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Assessment of Elastic Net-Logistic individual credit default risk based on random forest
Xi'an Gongcheng Daxue xuebao, 2021 Based on the credit data of South Germany, in terms of the characteristics of the high dimensionality of the explanatory variables, the rich types, and the unbalanced number of good and bad customers in the credit data, the factors that affect personal ...
Qian CHEN, Xingshi HE, Xinshe YANG
doaj +1 more source
Elastic-Net Regularization: Error estimates and Active Set Methods [PDF]
, 2009 This paper investigates theoretical properties and efficient numerical algorithms for the so-called elastic-net regularization originating from statistics, which enforces simultaneously l^1 and l^2 regularization.
Attouch H +13 more
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Bayesian elastic net based on empirical likelihood
Journal of Statistical Computation and Simulation, 2022 We propose a Bayesian elastic net that uses empirical likelihood and develop an efficient tuning of Hamiltonian Monte Carlo for posterior sampling. The proposed model relaxes the assumptions on the identity of the error distribution, performs well when the variables are highly correlated, and enables more straightforward inference by providing ...
Chul Moon, Adel Bedoui
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Sparse damage detection via the elastic net method using modal data
Structural Health Monitoring, 2021 The l1 regularization technique has been developed for damage detection by utilizing the sparsity feature of structural damage. However, the sensitivity matrix in the damage identification exhibits a strong correlation structure, which does not suffice ...
Rongrong Hou, Xiao-yang Wang, Yong Xia
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, 2011 The elastic net was introduced as a heuristic algorithm for combinatorial optimisation and has been applied, among other problems, to biological modelling. It has an energy function which trades off a fitness term against a tension term. In the original formulation of the algorithm the tension term was implicitly based on a first-order derivative.
Carreira-Perpiñán, Miguel Á. +1 more
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