Some Properties Related to Reduct of Consistent Decision Systems
Nguyễn Long Giang, János Demetrovics, Vũ Đức Thi, Phan Dang Khoa
Abstract
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Nguyễn Long Giang, János Demetrovics, Vũ Đức Thi, Phan Dang Khoa
Abstract
Open-access reader
Abstract Reduct of decision systems is the topic that has been attracting the interest of many researchers in data mining and machine learning for more than two decades. So far, many algorithms for finding reduct of decision systems by rough set theory have been proposed. However, most of the proposed algorithms are heuristic algorithms that find one reduct with the best classification quality. The complete study of properties of reduct of decision systems is limited. In this paper, we discover equivalence properties of reduct of consistent decision systems related to a Sperner-system. As the result, the study of the family of reducts in a consistent decision system is the study of Sperner-systems.
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Abstract Reduct of decision systems is the topic that has been attracting the interest of many researchers in data mining and machine learning for more than two decades. So far, many algorithms for finding reduct of decision systems by rough set theory have been proposed. However, most of the proposed algorithms are heuristic algorithms that find one reduct with the best classification quality. The complete study of properties of reduct of decision systems is limited. In this paper, we discover equivalence properties of reduct of consistent decision systems related to a Sperner-system. As the result, the study of the family of reducts in a consistent decision system is the study of Sperner-systems.
Key concepts: Reduct, Rough set, Decision system, Equivalence (formal languages), Computer science, Data mining, Decision table, Heuristic