Uncertainty Measures of Rules Based on Rough Set

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.