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A new hybrid algorithm for feature selection and its application to customer recognition

A new hybrid algorithm for feature selection and its application to customer recognition An important problem in customer recognition process is to select the most valid customer features. The authors present a new optimisation algorithm that combines a global optimisation algorithm called the nested partitions algorithm and the simulated annealing method. The resulting hybrid algorithm NP/SA retains the global perspective of the nested partitions algorithm and the local search capabilities of the simulated annealing method. A detailed application of the new algorithm to a customer recognition problem is also presented. The numerical results suggest that the new framework has great computation efficiency and convergence speed and is very efficient for a difficult customer feature selection problem. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Services Operations and Informatics Inderscience Publishers

A new hybrid algorithm for feature selection and its application to customer recognition

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
1741-539X
eISSN
1741-5403
DOI
10.1504/IJSOI.2009.023419
Publisher site
See Article on Publisher Site

Abstract

An important problem in customer recognition process is to select the most valid customer features. The authors present a new optimisation algorithm that combines a global optimisation algorithm called the nested partitions algorithm and the simulated annealing method. The resulting hybrid algorithm NP/SA retains the global perspective of the nested partitions algorithm and the local search capabilities of the simulated annealing method. A detailed application of the new algorithm to a customer recognition problem is also presented. The numerical results suggest that the new framework has great computation efficiency and convergence speed and is very efficient for a difficult customer feature selection problem.

Journal

International Journal of Services Operations and InformaticsInderscience Publishers

Published: Jan 1, 2009

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