糙集中近似质量的新认识

Recognition of Approximation Quality in Rough Sets

在粗糙集近似空间中提供了两个近似因子 :一个是对一个对象集近似的准确性因子α ,一个是属性集对另一个属性集的依赖程度因子或一个划分对另一个划分的近似因子γ 对于因子α可以给出精确性因子π与之比较 通过基于集合的距离度量公式 ,可以给出近似差错率来解释α ,γ和π 如果把数据空间从 1维拓广到k维 。

Rough approximation space provides two approximation factors: the accuracy of an approximation of an object set by a partition α and the accuracy of approximation of a partition by the other partition γ The precision of approximation π can be introduced to compare with α By introducing the distance measure based on sets, the factors α, γ and π can be interpreted Approximation space and its γ k can be obtained