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

  • Authors:
  • Luo Yan;Yu Changrui

  • Affiliations:
  • Institute of System Engineering, Shanghai Jiao Tong University, Shanghai, China;School of Information Management and Engineering, Shanghai University of Finance and Economics, Shanghai, China

  • Venue:
  • COCOA'07 Proceedings of the 1st international conference on Combinatorial optimization and applications
  • Year:
  • 2007

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Abstract

This paper proposes a novel hybrid algorithm for feature selection. This algorithm combines a global optimization algorithm called the simulated annealing algorithm based nested partitions (NP/SA). 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. We also present a detailed application of the new algorithm to a customer feature selection problem in customer recognition of a life insurance company and it is found to have great computation efficiency and convergence speed.