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A Different Quantity of Partition-Based Efficient Algorithm for Reduction of Attribute in Information Systems

机译:一种不同数量的基于分区的高效算法,用于减少信息系统中的属性

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摘要

Reduction of attribute is one of the key problems in rough set theory. In this paper, first, the notion of different quantity of partition is defined in information systems; from the viewpoint of which two new and rela- tively reasonable formulas measuring attribute signific- ance are designed for reducing searching space. Then the two formulas are used as heuristic information to develop an efficient attribute reduction algorithm, which can avoid repeatedly calculating important value of unimportant attributes; the theoretical analysis shows that this algorithm is much less time complexity than those existed algorithms. Finally, an example and experimental results demonstrate its feasibility and effectiveness, respectively.
机译:减少属性是粗糙集理论中的关键问题之一。在本文中,首先,在信息系统中定义了不同分区数量的概念;从两个新的和可重新定义合理的公式测量属性的观点来看,设计用于减少搜索空间。然后,两种公式用作启发式信息,以开发一个有效的属性还原算法,可以避免反复计算不重要属性的重要价值;理论分析表明,该算法比那些存在的算法要复杂得多。最后,一个例子和实验结果分别证明了其可行性和有效性。

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