An Incremental Updating Algorithm of the Computation of a Core Based on the Improved Discernibility Matrix
Ming Yang · Chinese Journal of Computers · 2006
Rough set theory is a new mathematical tool to deal with imprecise,incomplete and inconsistent data.Attributes reduction is one of important parts researched in rough set theory.The core of a decision table is the start point to many existing algorithms of attributes reduction.Many algorithms were proposed for the computation of a core.However,very little work has been done in updating of a core.Therefore,this paper introduces an incremental updating algorithm of the computation of a core based on discernibility matrix in the case of inserting,which only inserts a new row and column,or deletes one row and updates corresponding column when updating the decernibility matrix,so the updating efficiency of a core is remarkably improved.Theoretical analysis and experimental results show that the algorithms of this paper are efficient and effective.