Class-based Rough Approximation with Dominance Principle

TL;DR

This paper introduces a new class-based rough approximation method within the Dominance-based Rough Set Approach, enhancing decision analysis by focusing on singleton classes and exploring new reducts.

Contribution

It proposes a novel class-based rough approximation framework that extends existing DRSA models, including classical, VC-DRSA, and VP-DRSA, and investigates new class-based reducts.

Findings

Enhanced approximation accuracy for singleton classes

Development of new class-based reducts

Improved decision analysis in MCDA

Abstract

Dominance-based Rough Set Approach (DRSA), as the extension of Pawlak's Rough Set theory, is effective and fundamentally important in Multiple Criteria Decision Analysis (MCDA). In previous DRSA models, the definitions of the upper and lower approximations are preserving the class unions rather than the singleton class. In this paper, we propose a new Class-based Rough Approximation with respect to a series of previous DRSA models, including Classical DRSA model, VC-DRSA model and VP-DRSA model. In addition, the new class-based reducts are investigated.