【摘要】 Rough集作为一种处理模糊和不确定性问题的新颖方法已经在许多领域得到了广泛的应用。本文通过计算使决策表中的属性值区间化[3 ] ,删去冗余的决策规则 ,从而生成一种更具代表性的数据隐含式。利用上下距离函数和Rough决策因子代替统计方法或专家经验方法 ,在实际开发的系统中更具实用性。更多还原

【Abstract】 Rough sets as a new approach to handle vagueness and uncertainty have been widely used in many fields. This paper generates the interval values of attributes in decision table through computation, drops off the superfluous decision rules, so forms a much more representative data implication formula. Using distance functions with respect to rough upper and lower approximations and rough decision factor, instead of statistics or experts experiences methods can be more useful in the application.更多还原