A computational study of using genetic algorithms to develop intelligent decision trees

被引：0
|
作者：
Fu, ZW [1 ]
机构：
[1] Fannie Mae, Washington, DC 20016 USA
来源：
PROCEEDINGS OF THE 2001 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1 AND 2 | 2001年
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Decision tree algorithms have been widely used in dealing with data mining problems. However, scalability and efficiency are significant concerns in the implementation. We propose an innovative evolutionary computation approach, combining statistical sampling, genetic algorithm, and decision tree, to develop intelligent decision trees that alleviates some of these problems. Computational results show that our approach can obtain significantly better decision tree at lower sampling levels than does standard decision tree algorithm.
引用
收藏
页码：1382 / 1387
页数：6
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