A Heuristic Algorithm Based on Attribute Importance for Feature Selection

摘要：

In this paper we devote to study some feature selection of an information system in which redundant or insignificant attributes in data sets can be eliminated.An approach of importance gain function is suggested to evaluate the global average information gain associated with a subset of features.A heuristic algorithm on iterative criterion of feature selection on the significance of attributes is proposed to get the least reduction of attribute set in knowledge discovery.The feasibility of feature selection proposed here is validated by some of examples.

关键词： Rough set Importance Feature selection

作者: Xingbo Sun Xiuhua Tang Huanglin Zeng Shunyong Zhou

作者单位: Dept.of Electronic Engineering Sichuan University of Science & Engineering Zigong,Sichuan 643000,P.R Dept.of Material & Chemical Engineering Sichuan University of Science & Engineering Zigong,Sichuan 6

会议类型: 国际会议

会议名称: The Third International Conference on Rough Sets and Knowledge Tevhnology(RSKT 2008)(第三届粗糙集与知识技术国际会议)

会议地点: 成都

会议语种:英文

页码: 189-196

在线出版日期: 2008-05-17（万方平台首次上网日期，不代表论文的发表时间）