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基于混合遗传算法的分类规则挖掘方法研究

Classification Rule Mining Research Based on Hybrid Genetic Algorithm
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摘要 基于传统遗传算法的分类规则挖掘方法,通常存在挖掘出的规则质量不高,优化后种群中的冗余规则太多,分类准确率较低等问题.文中分析了分类规则挖掘原理,提出基于混合遗传算法的分类规则挖掘方法能够有效地克服上述缺点,从而提高分类规则挖掘的准确性. Traditional classification rule mining based on genetic algorithm usually exist the problem of low quality of the rules mined,redundant rules in the population are too much after optimization and classification accuracy is inaccuracy.This paper analyses the principles of classification rules mining,and proposed classification rules mining methods based on hybrid genetic algorithm,which can effectively overcome above disadvantages and improve the accuracy of classification rule mining.
作者 王祥瑞
出处 《吉林建筑工程学院学报》 CAS 2011年第6期68-71,共4页 Journal of Jilin Architectural and Civil Engineering
基金 吉林省教育厅"十二五"科学技术研究项目(2011第400号)
关键词 数据挖掘 分类规则 遗传算法 局部搜索 混合遗传算法 data mining classification rules genetic algorithm local search hybrid genetic algorithms
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参考文献3

  • 1M. V Fidelis, H. S. Lopes, A. A. Freitas, Discovering Comprehensible Classification Rules wth a Genetic Algorithm [ J ]. Evolutionary Computa- tion, 2000, Proceedings of the 2000 Congress on, Volume : 1, 16 -.19 July 2000, pp. 805 - 810.
  • 2Liuyu Yang, Dwi H. Widyantoro, Thomas loerger, John Yen, An Entropy - based Adaptive Genetic Algorithm for Learning Classification Rules [ J]. Evolutionary Computation, 2001. Proceedings of the 2001 Congress on, Volume: 2, 27 - 30 May 2001, pp. 790 -796.
  • 3Deborah R Carvalho, Alex A. Freitas, A hybrid decision tree/genetic algorithm method for data mining[ J]. Information Sciences, Volume I63, Issue: 1 -3, June 14, 2004, pp. 13 -35.

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