基于粗集的规则不确定性量度  

Uncertainty Measures of Rules Based on Rough Set

作　　者：凌方[1] 

机构地区：[1]南京工业职业技术学院信息工程系,江苏南京210046

出　　处：《南京工业职业技术学院学报》2007年第2期32-35,共4页Journal of Nanjing Institute of Industry Technology

摘　　要：在对粗集及其相关理论的研究基础上,给出了一种基于推广粗集模型和信息熵的规则不确定性量度及其相关定理的证明,同时在此基础上还提出了一种规则噪音处理方法,实验结果证明该不确定性量度适用于评价从有噪音数据中提取的规则。Data Mining has been an urgent need because of increasing size of current databases. Rough Set theory has become an important method for data mining due to its unique advantage in knowledge discovery. An information entropy-based uncertainty measure is presented first based on generalized rough set model in this paper. Second, this paper puts forward a new method to resolve noisy rules. The empirical result illustrates that the uncertainty measure is suitable for evaluating rules retrieved from noisy data.

关 键 词：粗集 噪音 不确定性量度 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]