基于相对知识量重要度的属性约简算法

Attribute Reduction Algorithm based on the Relative Importance Degree

在有效处理噪声数据的基于区分能力大小的启发式算法的基础上,引入了属性的相对知识量重要度的概念.以属性相对知识量重要度为启发式信息,提出了一种属性约简算法,通过实例证明了该算法的有效性.

Based on Xu Yan who can effectively deal with noise data based on the ability to distinguish the size of the heuristic algorithm is introduced on the basis of relative attribute, which is an important concept, is an important attribute relative heuristic information, this paper puts forward a kind of attribute reduction algorithm, through the examples showing the effectiveness of the proposed algorithm.