摘要
为了从大量数据中获取有用的知识,提出了基于粗集与神经网络技术的数据挖掘方法。首先利用粗集理论消除冗余的属性,得到数据集的一些规则,然后利用这些规则构造神经网络,利用神经网络技术完善粗糙规则。文章就这一技术的研究方法作了综述,并提出了改进的粗集约简方法.
In order to obtain useful knowledge from large database, an approach to data mining which integrates neural network and rough sets is presented. Present rough set to remove the redundant attribute and acquire a set of rough rule. Then the structure and model are designed according to these rules,and mend original rough rules. Here summarizes this theory, and presents an improved algorithm of attribute reduction . Finally, the paper puts forward a few of open question to be solved in the future studies.
出处
《微机发展》
2003年第a02期43-45,共3页
Microcomputer Development
