An Algorithm for Computing All Rough Set Constructs for Dimensionality Reduction

Yanir González-Díaz (), José Fco. Martínez-Trinidad, Jesús A. Carrasco-Ochoa and Manuel S. Lazo-Cortés
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Yanir González-Díaz: Department of Computer Science, Instituto Nacional de Astrofísica, Óptica y Electrónica (INAOE), Puebla 72840, Mexico
José Fco. Martínez-Trinidad: Department of Computer Science, Instituto Nacional de Astrofísica, Óptica y Electrónica (INAOE), Puebla 72840, Mexico
Jesús A. Carrasco-Ochoa: Department of Computer Science, Instituto Nacional de Astrofísica, Óptica y Electrónica (INAOE), Puebla 72840, Mexico
Manuel S. Lazo-Cortés: Graduate Division, Tecnológico Nacional de México/IT Tlalnepantla, Tlalnepantla de Baz 54070, Mexico

Mathematics, 2023, vol. 12, issue 1, 1-19

Abstract: In rough set theory, a construct is an attribute subset with the same ability to discern objects belonging to different classes as the whole set of attributes, while maintaining the similarity between objects belonging to the same class. Although algorithms for reducts computation can be adapted to compute constructs, practical problems exist where these algorithms cannot compute all constructs within a reasonable time frame. Therefore, this paper introduces an algorithm for computing all constructs of a decision system. The results of experiments with various decision systems (both artificial and real-world) suggest that our algorithm is, in most cases, faster than the state-of-the-art algorithms when the simplified binary discernibility–similarity matrix has a density of less than 0.29.

Keywords: rough sets; constructs; fast algorithms; feature selection (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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