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A general reduction algorithm for relation decision systems and its applications

机译：关系决策系统的通用约简算法及其应用

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This paper studies the attribute reduction problem for general relation decision systems. We propose a new discernibility matrix to solve this problem. Combining the discernibility matrix and a recently proposed fast algorithm, we propose a simple and unified attribute reduction algorithm for relation decision systems that is not contingent on the consistency of relation decision systems. We derive the reduction algorithm for the special cases of complete, incomplete, and numerical decision tables. As an application, we transform the attribute reduction of relation decision systems into one for covering decision systems. This gives a convenient and effective reduction algorithm for covering decision systems. The reduction results obtained using University of California Irvine data sets show that the proposed algorithm is simple and efficient. Moreover, the proposed algorithm enables the results of classical attribute reduction approaches to be reinterpreted, giving them far greater unification and generality. (C) 2016 Elsevier B.V. All rights reserved.
机译：本文研究了通用关系决策系统的属性约简问题。我们提出了一个新的可分辨矩阵来解决这个问题。结合区别矩阵和最近提出的快速算法，我们提出了一种简单而统一的关系决策系统属性约简算法，该算法不依赖于关系决策系统的一致性。我们针对完全，不完全和数值决策表的特殊情况导出归约算法。作为一种应用程序，我们将关系决策系统的属性约简转换为一个覆盖决策系统的属性。这为覆盖决策系统提供了一种方便有效的归约算法。使用加州大学尔湾分校的数据集获得的约简结果表明，该算法简单有效。此外，所提出的算法使经典属性约简方法的结果得以重新解释，从而使它们具有更大的统一性和通用性。 （C）2016 Elsevier B.V.保留所有权利。

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