Wan Mohd. Rosly, Wan Nur Shaziayani (2011) Variable selection using least angle regression. Masters thesis, Universiti Teknologi Malaysia, Faculty of Science.
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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) |
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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 |
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