Boundary Variable Precision Dominance-Based Rough Set Approach in Multicriteria Sorting Problems

Abstract

This paper provides a novel method of boundary variable precision dominance-based rough set approach (BVP-DRSA) to solve multicriteria sorting problem that differs from usual classification problems since it takes into account preference orders in the description of objects by condition and decision attributes. The major contribution of our BVP-DRSA method is that it combines variable precision and dominance-based rough set approach (DRSA). This approach is different from the dominance-based rough set approach (DRSA) because it takes boundary into account and can deal with boundary directly. Comparative experiments form datasets of UCI and empirical results shows that our BVP-DRSA is far more efficient than directly using already known classing algorithms and DRSA.