关键词: 属性约简, 粗糙集理论, 类间重合度, 类间区分度

Abstract: Attribute reduction is one of the most important research issues in the rough set theory. In recent years, the attribute reduction problem under the rough set theory has attracted many scholars?? attention. However, most of the attribute reduction methods are proposed based on the indiscernibility relations or the discernibility relations, and the performance of the attribute reduction only depends on the changes of the equal classes or the approximation sets, but the changes between different clusters of objects that do not have an equivalence relationship are ignored. Therefore, this paper proposes a notion of the inter-class separability. Compared with the equivalence class or the approximation sets, it can reflect the degree of distinction between different classes as the attributes change. This paper explains and defines the inter-class separability and the inter-class coincidence degree, and proposes an inter-class separability based attribute reduction method by considering the heuristic search strategy. Moreover, the experimental results indicate the efficiency of the proposed attribute reduction method.

Key words: attribute reduction, rough set theory, inter-class coincidence degree, inter-class separability