计算机工程与应用 ›› 2007, Vol. 43 ›› Issue (31): 156-158.

• 数据库与信息处理 • 上一篇    下一篇

基于遗传算法的粗糙集属性约简算法

颜 艳,杨慧中   

  1. 江南大学 通信与控制工程学院,江苏 无锡 214122
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2007-11-01 发布日期:2007-11-01
  • 通讯作者: 颜 艳

Rough set attribute reduction algorithm based on GA

YAN Yan,YANG Hui-zhong   

  1. School of Communication & Control Engineering,Jiangnan University,Wuxi,Jiangsu 214122,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2007-11-01 Published:2007-11-01
  • Contact: YAN Yan

摘要: 针对粗糙集理论核心内容之一的知识约简问题,提出了一种基于遗传算法的粗糙集属性约简算法。利用条件熵计算属性间的相关性,并将其引入到适值函数中,可以保证所求约简含有较少的属性而且属性间的相关性较小。实验证明,它可以得到比较理想的结果,对UCI机器学习数据集的测试结果也验证了算法的有效性。

Abstract: One of rough set theory essence is knowledge reduction. A kind of knowledge relative reduction algorithm based on GA was proposed. Conditional information entropy was used to compute relevance of attributes and it was used in fitness function to assure reduction has fewer attributes and relevance of attributes. The test results by UCI Machine Learning Data Set show this algorithm is effective.