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  • 标题:A Model of Immune Gene Expression Programming for Rule Mining
  • 本地全文:下载
  • 作者:T. Zeng ; C. Tang ; Y. Xiang
  • 期刊名称:Journal of Universal Computer Science
  • 印刷版ISSN:0948-6968
  • 出版年度:2007
  • 卷号:13
  • 期号:10
  • 页码:1484-1484
  • 出版社:Graz University of Technology and Know-Center
  • 摘要:Rule mining is an important issue in data mining. To address it, a novel Immune Gene Expression Programming (IGEP) model was proposed. Concepts of rule, gene, immune cell, and antibody were formalized. The dynamic evolution models and the corresponding recursive equations of immune cell, self, immune-tolerance were built. The novel key techniques of IGEP were presented. Experiment results showed that the new method has good stability, scalability and flexibility. It can discover traditional association rule, non-traditional rule including connective "OR" or "NOT", and meta-rule of strong rule. Furthermore, it can perform well in constrained pattern mining.
  • 关键词:artifical immune system, data mining, evolutionary algorithm, gene expression programming, meta-rule, rule
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