关键词: 决策粗糙集, 属性约简, 正域, 差别矩阵

Abstract: For Decision-Theoretic Rough Set （DTRS） models, the positive region change rules are analyzed when removing attributes from conditional attribute set. That is, the positive region not only may be larger, but also can be unchanged or smaller with respect to the decreasing of attributes. The existing attribute reducts related to positive regions in DTRS models are discussed and analyzed. Then a new type of positive region preservation attribute reduct in DTRS models is proposed. An example is given to show that the method based on discernibility matrix can’t get all of positive region preservation reducts as in classical rough set models. It shows that the attribute reduct methods in classical rough set models are completely different from the ones in DTRS models and can’t extend the methods to DTRS parallelly. The results above give a summary and provide a theoretical basis for the attribute reduct research in DTRS models in the future.

Key words: decision-theoretic rough set, attribute reduct, positive region, discernibility matrix