摘要
基于粗糙集的数据挖掘,提出了通过统计方法降低边界元素的不确定性程度的方法。该方法依据边界元素的统计规律从属性约简所产生的最小覆盖中选择合适的覆盖形成规则,从而更充分地利用属性约简和数据仓库中的数据资源,提高基于粗糙集的数据挖掘的效果。
This paper is focused on studying rough set based data mining.A method based on statistics to reduce uncertain degree of border elements of the rough set is presented.According to statistics rules of the border elements, it selects appropriate minimum cover producing by related attribute reduction to form rules.So,it makes better use of the attribute reduction and data resource of data warehouse.
出处
《计算机工程与应用》
CSCD
北大核心
2010年第7期131-133,共3页
Computer Engineering and Applications
关键词
粗糙集
数据挖掘
属性约简
条件概率
rough set
data mining
attribute reducte
condition probability
