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Attribute reduction based on improved discernibility matrix

机译:基于改进的区分矩阵的属性约简

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摘要

The attribute reduction based on information entropy is different to that based on positive region in inconsistent information system. The problem of discernibility matrix in algebra view is analyzed, and an new discernibility matrix based on information entropy is proposed in this paper. This algorithm considers whether the objects compared are consistent, analyses in detail the degree of inconsistency and the distributing proportion of their conditional equivalent classes in decision classes, and the reduction based on information entropy is acquired finally. The theoretic analysis and simulation instance shows that this algorithm is feasible and effective in practice.
机译:在信息系统不一致的情况下,基于信息熵的属性约简与基于正区域的属性约简不同。分析了代数视角下的区分矩阵问题,提出了一种新的基于信息熵的区分矩阵。该算法考虑比较对象是否一致,详细分析不一致程度和条件等价类在决策类中的分配比例,最终获得基于信息熵的约简。理论分析和仿真实例表明,该算法在实际中是可行和有效的。

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