论文部分内容阅读
In Rough Set Theory,dependency degree refers to the degree that one attribute subset depends on another.Traditional dependency degree is computed through counting only deterministic rules by means of the equivalence relations.Some further studies redefined the dependency functions through consideration of both deterministic and indeterministic rules.To apply the function,it is important to associate it with efficient and effective computational methods.In this paper,we design a binary representation of(in)discernibility matrices and propose an algorithm to calculate the redefined dependency functions.Since logical operations instead of comparison ones are employed,the new algorithm is quite efficient.The proposed algorithm is compared with a previous work which has already taken advantage of discernibility matrices to improve the efficiency.Experimental results show that the new algorithm defeats its counterpart in large information systems.