Algorithms based on general discernibility matrix for computation of a core and attribute reduction

Attributes reduction is one of important parts researched in rough set theory.Therefore,in this paper,after proposing a concept of general discernibility matrix,both computation of a core and attribute reduction algorithms based on general discernibility matrix are introduced.The newly proposed framework can effectively avoid discretizing the continuous-valued attributes and be easily incorporated into other machine learning methods.Theoretical analysis shows the effectiveness of the algorithm.