Universiti Teknologi Malaysia Institutional Repository

Variable selection using least angle regression

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)
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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