一种基于粗糙集理论的规则获取算法

Rule generation approach based on rough set theory

获取规则是数据挖掘中的一项重要技术 ,根据粗糙集理论及决策值归纳函数的概念 ,可以把不相容的决策系统转化为相容的决策系统 ,并提出规则参数的合并方法 .在此基础上 ,利用决策矩阵和决策函数 ,提出了一种在决策系统中获取规则的算法 .同传统的算法相比 ,该算法得出的规则集没有信息丢失的现象发生 .最后以例子作了说明 .

Rule generation is an important technology in data mining. In this paper, based on rough set theory, using the concept of generalized decision attribute function or uncertain class, an inconsistent decision system is transformed to one that is consistent as an initial preprocessing step. On the basis of this, by means of discernibility matrix and decision function, a rule generation algorithm is presented. The algorithm can generate all decision rules directly, instead of computing all the reducts of decision system. Furthermore, the obtained rule set using the algorithm keeps all useful information, which is different from that using some other algorithm. In the end, an example illustrates that the algorithm is reasonable and effective.