Wan Mohd. Rosly, Wan Nur Shaziayani (2011) Variable selection using least angle regression. Masters thesis, Universiti Teknologi Malaysia, Faculty of Science.
|
PDF
69kB |
Official URL: http://dms.library.utm.my:8080/vital/access/manage...
Abstract
The least-angle regression (LARS) (Efrron, Hastie, Johnstone, and Tibshirani, 2004) is a technique used with the absence of data that consist of many independent variables. Suppose we expect a response variable to be determined by a linear combination of a subset of potential covariates. Then the LARS algorithm provides a means of producing an estimate of which variables to include, as well as their coefficients. The MATLAB programming codes are developed in order to solve the algorithms systematically and effortlessly.
| Item Type: | Thesis (Masters) |
|---|---|
| Additional Information: | Thesis (Sarjana Sains (Matematik)) - Universiti Teknologi Malaysia, 2011; Supervisor : Assoc. Prof. Dr. Ismail Mohammad |
| Uncontrolled Keywords: | least-angle regression, MATLAB, angle regression |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Science |
| ID Code: | 48703 |
| Deposited By: | Narimah Nawil |
| Deposited On: | 20 Oct 2015 03:05 |
| Last Modified: | 17 Jun 2020 07:30 |
Repository Staff Only: item control page
