Innovations to Attribute Reduction of Covering Decision System Based on Conditional Information Entropy

• Autores: Xiuyun Xia, Hao Tian, Ye Yang
• Localización: Applied Mathematics and Nonlinear Sciences, ISSN-e 2444-8656, Vol. 8, Nº. 1, 2023, págs. 2103-2116
• Idioma: inglés
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• Resumen

  • Traditional rough set theory is mainly used to reduce attributes and extract rules in databases in which attributes arecharacterised by partitions, which the covering rough set theory, a generalisation of traditional rough set theory, covers.In this article, we posit a method to reduce the attributes of covering decision systems, which are databases incarnatedin the form of covers. First, we define different covering decision systems and their attributes’ reductions. Further, wedescribe the necessity and sufficiency for reductions. Thereafter, we construct a discernible matrix to design algorithmsthat compute all the reductions of covering decision systems. Finally, the above methods are illustrated using a practicalexample and the obtained results are contrasted with other results