Dominance relation and rules in an incomplete ordered information system

TLDR

Rough sets theory, originally developed for classification and prediction, has been extended to dominance-based rough sets to handle ordering of objects by replacing indiscernibility with a dominance relation. The study introduces a dominance-based rough sets framework for reasoning in incomplete ordered information systems and proposes a knowledge reduction technique that removes only non‑essential information relative to object ordering or decision rules. The framework applies dominance-based rough sets to incomplete ordered decision tables, enabling reasoning and knowledge reduction by eliminating redundant information. Using this approach, decision rules can be extracted directly from incomplete ordered decision tables. © 2005 Wiley Periodicals, Inc., Int J Int Syst 20:13–27, 2005.

Abstract

Rough sets theory has proved to be a useful mathematical tool for classification and prediction. However, as many real-world problems deal with ordering objects instead of classifying objects, one of the extensions of the classical rough sets approach is the dominance-based rough sets approach, which is mainly based on substitution of the indiscernibility relation by a dominance relation. In this article, we present a dominance-based rough sets approach to reasoning in incomplete ordered information systems. The approach shows how to find decision rules directly from an incomplete ordered decision table. We propose a reduction of knowledge that eliminates only that information that is not essential from the point of view of the ordering of objects or decision rules. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 13–27, 2005.