Multi-objective feature selection by using NSGA-II for customer churn prediction in telecommunications

Authors:
Bingquan Huang;B. Buckley;T. -M. Kechadi
Affiliations:
School of Computer Science and Informatics, University College Dublin, Belfield, Dublin 4, Ireland;Eircom Limited, 1 Heuston South Quarter, St. John's Road, Dublin 8, Ireland;School of Computer Science and Informatics, University College Dublin, Belfield, Dublin 4, Ireland
Venue:
Expert Systems with Applications: An International Journal
Year:
2010

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Abstract

This paper proposes a new multiobjective feature selection approach for churn prediction in telecommunication service field, based on the optimisation approach NSGA-II. The basic idea of this approach is to modify the approach NSGA-II to select local feature subsets of various sizes, and then to use the method of searching nondominated solutions to select the global nondominated feature subsets. Finally, the method FBSM which yields the fitness thresholds is proposed to choose the global solutions with the lowest ranks as the final solutions. In order to evaluate the proposed approach, experiments were carried out and the experimental results show that the proposed feature selection approach is efficient for churn prediction with multiobjectives.