Incremental updating algorithm for core computing in dominance-based rough set model

This paper analyzes incremental updating for core computing in a dominance-based rough set model, which extends previous reduct studies in capability of dynamic updating and dominance relation. Then we redefine the dominance discernibility matrix and present an incremental updating algorithm. In this algorithm, when new samples arrive, the proposed solution only involves a few modifications to relevant rows and columns in the dominance discernibility matrix instead of recalculation. Both of theoretical analysis and experimental results show that the algorithm is effective and efficient in dynamic computation.