Skip Navigation

IMA Journal of Management Mathematics 2007 18(2):191-206; doi:10.1093/imaman/dpm012
This Article
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Pacheco, J.
Right arrow Articles by Nuñez, L.
Right arrow Search for Related Content
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The authors 2007. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.

Use of VNS and TS in classification: variable selection and determination of the linear discrimination function coefficients

Joaquín Pacheco**,1, Silvia Casado***,2 and Laura Nuñez****,3

1 Departamento de Economía Aplicada, Universidad de Burgos, Plaza Infanta Elena s/n 09001 Burgos, Spain, 2 Departamento de Economía Aplicada, Universidad de Burgos, Plaza Infanta Elena s/n 09001 Burgos, Spain, 3 Departamento de Finanzas, Instituto de Empresa, Serrano 105, 28006 Madrid, Spain

** Email: jpacheco{at}ubu.es

*** Email: scasado{at}ubu.es

**** Email: laura.nunez{at}ie.edu


  Abstract

In this paper, we discuss the problem of variable selection and the determination of the coefficients for these variables that provide the best linear discrimination function with the objective of obtaining a high classification success rate. Given the relation that exists between both problems, they will be performed simultaneously. In order to resolve them, two algorithms based on the metaheuristic approaches variable neighbourhood search and tabu search have been designed. These methods have proved to obtain significantly better results than two of the most classic methods for obtaining discriminant linear functions: classic discriminant analysis and logistic regression.

Keywords: variable neighbourhood search; tabu search; variable selection; classification; linear discrimination

Received on April 2006. accepted on 2 February 2007.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?




Disclaimer:
Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.