Sampling Based on Genetic Algorithm for Data Mining

被引：0
|
作者：
Wang Jianyong [1 ]
Huang Yu [1 ]
Hu Bin [1 ]
Wei Xiaomei [1 ]
机构：
[1] Huazhong Agr Univ, Coll Sci, Wuhan 430070, Hubei Province, Peoples R China
来源：
INFORMATION-AN INTERNATIONAL INTERDISCIPLINARY JOURNAL | 2012年 / 15卷 / 09期
关键词：
Genetic algorithm; Association rules; Accuracy;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Collecting a large initial sample set from a huge data set, and then distilling a smaller sample set from the initial set in the same accuracy can greatly enhance the speeds of data mining algorithms. As the distilling process is proved as a NP-hard problem, the two-phase sampling algorithm FAST adopts a kind of geed method. Adopting genetic algorithm in sample distilling, a sampling algorithm SGA is presented in this paper, which performs better than popular sampling algorithms including FAST in the experiment.
引用
收藏
页码：3667 / 3672
页数：6
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