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A unified approach to reducts in dominance-based rough set approach

机译:减少基于优势的粗糙集方法的统一方法

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The Dominance-based Rough Set Approach (DRSA), which is an extension of the Rough Set Approach (RSA), analyzes a sorting problem for a given data set. Attribute reduction is one of major topics in RSA as well as DRSA. By attribute reduction, we can find an important attribute set, which is called a reduct. In this paper, we propose a new approach to reducts in DRSA. A few kinds of reducts have been already proposed in DRSA, therefore, we clarify relations among the proposed and previous ones. We prove that they are consolidated into four kinds. Moreover, we show that all kinds of reducts can be enumerated based on two discernibility matrices. Keywords Rough sets - Dominance-based rough set approach - Attribute reduction - Discernibility matrix
机译:基于优势的粗糙集方法(DRSA)是粗糙集方法(RSA)的扩展,它分析了给定数据集的排序问题。属性约简是RSA和DRSA中的主要主题之一。通过属性归约,我们可以找到一个重要的属性集,称为归约。在本文中,我们提出了一种减少DRSA的新方法。在DRSA中已经提出了几种还原方法,因此,我们澄清了所提出的还原方法与先前方法之间的关系。我们证明它们被合并为四种。此外,我们表明,可以基于两个区分矩阵来枚举所有类型的归约。关键词粗糙集-基于优势的粗糙集方法-属性约简-区分矩阵

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