The Application of MPC-GEP in Classification Rule Mining

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 269)

Abstract

Gene Expression Programming algorithm Based on Multi-Phenotype Chromosomes (MPC-GEP) makes it possible for single chromosome to be decoded into multiple expression trees, that is to say, it will contain multiple possible solutions so that the possibility for population to involve optimal solution will be increased. In this paper, MPC-GEP algorithm will be introduced and then be applied to classification rule mining. The experiment results show that compared with classification method based on GEP, MPC-GEP algorithm can improve the efficiency and the reliability of classification rule mining.

Keywords

Gene expression programming (GEP)  MPC-GEP  Classification rule mining 

Notes

Acknowledgments

This paper is the partial achievement of project 2013CB329504 supported by National key basic research and development program (973 program), project 61272261 supported by National natural science foundation of China, and project Y1110152 supported by the Natural Science Fund of Zhejiang Province.

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.College of Computer Science and TechnologyZhejiang UniversityHangzhouPeople’s Republic of China

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