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Improving Indiscernibility Matrix Based Approach for Attribute Reduction

机译:改进的基于不可区分矩阵的属性约简方法

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The problem of finding all reducts of the attribute set of a data table has often been studied in rough set theory by using the notion of discernibility matrix. An alternative version based on the indiscernibility matrix has been used for this problem to a lesser extent due to its space and time complexity. This paper improves the indiscernibility matrix based approach for computing all reducts. Only indiscernibility matrix cells as well as subsets of the attribute set necessary for computing reducts are processed. The experiments reported in this paper show that the improved version uses less memory to store partial results and can find reducts in a shorter time.
机译:在粗糙集理论中,经常通过使用可分辨矩阵的概念来研究寻找数据表属性集的所有约简的问题。由于其时空复杂性,基于不可分辨矩阵的替代版本已在较小程度上用于此问题。本文改进了基于不可区分矩阵的计算所有折减的方法。仅处理不可区分的矩阵单元以及计算归约所需的属性集的子集。本文报道的实验表明,改进的版本使用较少的内存来存储部分结果,并且可以在更短的时间内找到还原。

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