G-2013-109
Generalized Elastic Net Regression
, , and BibTeX reference
This work presents a variation of the elastic net penalization method. We propose applying a combined l
1 and l
2 norm penalization on a linear combination of regression parameters. This approach is an alternative to the l
1-penalization for variable selection, but takes care of the correlation between the linear combination of parameters. We devise a path algorithm fitting method similar to the one proposed for the least angle regression. Furthermore, a one-shot estimation technique of l
2 regularization parameter is proposed as an alternative to cross-validation. A simulation study is conducted to check the validity of the new technique.
Published December 2013 , 10 pages
Publication
Jan 2013
Generalized elastic net regression
, , and
JSM Proceedings, 3457–3464, 2013
BibTeX reference