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A new method of attribute reduction of covering rough sets

Tian Yang, Qingguo Li, Bilei Zhou

Open publisher page 3 citations

Abstract

In rough set theory, the discernibility matrix is a classical method to compute all attribute reducts. However, it is useless in certain circumstances as shown in this paper. As a result, a new method, namely related family, is developed initially in this paper. As a more powerful tool than the discernibility matrix, relate family can compute all attribute reducts of covering generalized rough sets, not only in the cases the discernibility matrix is usually employed for, but also for more comprehensive instances to which the discernibility matrix is not applicable.

About this research paper

What this paper is about

In rough set theory, the discernibility matrix is a classical method to compute all attribute reducts. However, it is useless in certain circumstances as shown in this paper. As a result, a new method, namely related family, is developed initially in this paper. As a more powerful tool than the discernibility matrix, relate family can compute all attribute reducts of covering generalized rough sets, not only in the cases the discernibility matrix is usually employed for, but also for more comprehensive instances to which the discernibility matrix is not applicable.

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OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

In rough set theory, the discernibility matrix is a classical method to compute all attribute reducts. However, it is useless in certain circumstances as shown in this paper. As a result, a new method, namely related family, is developed initially in this paper. As a more powerful tool than the discernibility matrix, relate family can compute all attribute reducts of covering generalized rough sets, not only in the cases the discernibility matrix is usually employed for, but also for more comprehensive instances to which the discernibility matrix is not applicable.

Key concepts: Rough set, Reduction (mathematics), Matrix (chemical analysis), Set (abstract data type), Mathematics, Computer science, Data mining, Algorithm

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