A Note on Coding and Standardization of Categorical Variables in (Sparse) Group Lasso Regression

DOI10.48550/arXiv.1805.06915zbMath1437.62276arXiv1805.06915OpenAlexW2971287324WikidataQ127301634 ScholiaQ127301634MaRDI QIDQ146016

Martin Slawski, Felicitas Detmer, Martin Slawski, Juan R. Cebral, Felicitas J. Detmer

Publication date: 17 May 2018

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1805.06915

zbMATH Keywords

regularizationvariable selectiongroup Lassostandardization

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Ridge regression; shrinkage estimators (Lasso) (62J07)

Related Items

grplassocat

Uses Software

• glinternet
• catdata

Cites Work

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• Oracle inequalities and optimal inference under group sparsity
• The benefit of group sparsity
• Standardization and the Group Lasso Penalty
• The Group Lasso for Logistic Regression
• Model Selection and Estimation in Regression with Grouped Variables
• A unified framework for high-dimensional analysis of \(M\)-estimators with decomposable regularizers