DocumentCode
948040
Title
A Fast Tracking Algorithm for Generalized LARS/LASSO
Author
Keerthi, S. Sathiya ; Shevade, Shirish
Author_Institution
Media Studios North, Burbank
Volume
18
Issue
6
fYear
2007
Firstpage
1826
Lastpage
1830
Abstract
This letter gives an efficient algorithm for tracking the solution curve of sparse logistic regression with respect to the regularization parameter. The algorithm is based on approximating the logistic regression loss by a piecewise quadratic function, using Rosset and Zhu´s path tracking algorithm on the approximate problem, and then applying a correction to get to the true path. Application of the algorithm to text classification and sparse kernel logistic regression shows that the algorithm is efficient.
Keywords
pattern classification; regression analysis; text analysis; generalized least angle regression; least absolute shrinkage; path tracking algorithm; piecewise quadratic function; selection operator; sparse kernel logistic regression; sparse logistic regression; text classification; Generalized least angle regression (LARS); least absolute shrinkage and selection operator (LASSO); sparse logistic regression;
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/TNN.2007.900229
Filename
4359182
Link To Document