A method of data classification based on parallel genetic algorithm

Authors:
Yuexiang Shi;Zuqiang Meng;Zixing Cai;B. Benhabib
Affiliations:
School of information engineer, XiangTan University, XiangTan, China;School of information engineer, Central South University, ChangSha, China;School of information engineer, Central South University, ChangSha, China;Department of Mechanical and Industrial Engineering, Toronto University, Ontario, Canada
Venue:
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part I
Year:
2005

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Abstract

An effectual genetic coding is designed by constructing full-classification rule set. This coding results in full use of all kinds of excellent traits of genetic algorithm in data classification. The genetic algorithm is paralleled in process. So this leads to the improvement of classification and its ability to deal with great data. Some defects of current classifier algorithm are tided over by this algorithm. The analysis of experimental results is given to illustrate the effectiveness of this algorithm.