Learn More
Rough set theory has witnessed great success in data mining and knowledge discovery, which provides a good support for decision making on a certain data. However, a practical decision problem always shows diversity under the same circumstance according to different personality of the decision makers. A simplex decision model can not provide a full(More)
—The decision-theoretic rough set model (DTRSM) was proposed two decades ago. In this paper, the development of DTRSM, including the theories and the potential applications, are reviewed. With respect to the two semantic issues of DTRSM, three-way decision procedure, attribute reduction methods and potential applications of DTRSM are examined. This paper(More)
The monotonicity of positive region in PRS (Pawlak Rough Set) and DTRS (Decision-Theoretic Rough Set) are comparatively discussed in this paper. Theoretic analysis shows that the positive region in DTRS model may expand with the decrease of the attributes, which is essentially different from that of PRS model and leads to a new definition of attribute(More)
A novel interval set approach is proposed in this paper to induce classification rules from incomplete information table, in which an interval-set-based model to represent the uncertain concepts is presented. The extensions of the concepts in incomplete information table are represented by interval sets, which regulate the upper and lower bounds of the(More)