摘要
文章给出了一个基于粗糙集理论的属性相关性的新定义,并在此基础上给出了基于属性相关性的属性约简新方法。本算法不但能过滤掉属性集合中的无关属性,而且能有效地找到属性集合中的冗余属性,从而得到满意的属性约简。对UCI机器学习数据集的测试结果也验证了算法的有效性。
This article gives a new concept of feature correlation based on Rough Sets Theory.And according this new concept,a new algorithm to finding feature reduct is introduced,This algorithm not can only remove irrelevant features,it also can find redundant feature with high feature correlation,The test result by UCI Machine Learning Data Set show this algorithm is effective.
出处
《计算机工程与应用》
CSCD
北大核心
2005年第28期55-57,共3页
Computer Engineering and Applications
关键词
粗糙集
属性约简
冗余属性
属性相关性
rough sets,feature reduct,redundant feature,feature correlation
