Matlab implementation of LASSO, LARS, the elastic net and SPCA |
| | Abstract | UPDATE: Download the latest code and documentation from http://www.imm.dtu.dk/projects/spasm
There are a number of interesting variable selection methods available beside the regular forward selection and stepwise selection methods. Such approaches include LASSO (Least Absolute Shrinkage and Selection Operator), least angle regression (LARS) and elastic net (LARS-EN) regression. There also exists a method for calculating principal components with sparse loadings. This software package contains Matlab implementations of these functions. The standard implementations of these functions are available as add-on packages in S-Plus and R. | | Keywords | LASSO, LARS, SPCA, Matlab, Elastic Net, Sparse, Sparsity, Variable selection | | Type | Software | | Year | 2005 Month June | | Publisher | Informatics and Mathematical Modelling, Technical University of Denmark, DTU | | Address | Richard Petersens Plads, Building 321, DK-2800 Kgs. Lyngby | | Note | Version 2.0 | | Electronic version(s) | [zip] | | BibTeX data | [bibtex] | | IMM Group(s) | Image Analysis & Computer Graphics |
|