基于差别矩阵的属性约简算法

Ruizhi Wang, D. Miao, Guirong Hu
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引用次数: 15

摘要

在粗糙集理论中,已经证明了寻找信息系统或决策表的最小约简是一个np完全问题。因此,现有的知识约简算法很难得到最简洁的规则集。提出了一种基于差别矩阵的次优约简算法。总的来说,我们的方法在最小约简方面优于现有的方法。然而,我们发现现有的最小约简搜索算法对于信息系统或决策表中的属性约简是不完整的。通过分析,我们提出了一个关于最小约简算法完备性的猜想
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Discernibility Matrix Based Algorithm for Reduction of Attributes
In rough set theory, it has been proved that finding the minimal reduct of information systems or decision tables is a NP-complete problem. Therefore, it is hard to obtain the set of the most concise rules by existing algorithms for reduction of knowledge. In this paper, the method of finding sub-optimal reduct based on discernibility matrix is proposed. In general, our method is better than existing methods with respect to the minimal reduct. However, we find that existing minimal reduct searching algorithms are incomplete for reduction of attributes in information systems or decision tables. Through analysis, we present a conjecture about the completeness of the minimal reduct algorithm
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