Abstract: Now the existing classical reduction algorithms have high time consumption,especially on the large scale datasets.To handle this problem,this paper introduced weights into the concept of attribute reduction,where weight is the measure of attribute significance.By building optimization problem about weights,it is fond that the attribute dependency degree is just the optimal solution of the weights.As a result,this paper proposed a reduction algorithm based on ranked weights,which significantly accelerate attribute reduction.Numerical experiments demonstrate that the proposed algorithm is suitable on large scale datasets,especially on the datasets with high dimension.

Key words: Fuzzy rough sets,Attribute reduction,Weights,High dimension datasets