《计算机应用研究》|Application Research of Computers

基于矩阵保留策略的邻域粗糙集属性约简算法

Neighborhood rough set attribute reduction algorithm based on matrix reservation strategy

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作者 高阳,刘遵仁,纪俊
机构 青岛大学 计算机科学技术学院,山东 青岛 266071
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文章编号 1001-3695(2019)12-010-3570-04
DOI 10.19734/j.issn.1001-3695.2018.05.0390
摘要 在基于邻域粗糙集的属性约简算法中,正域计算是保证其有效性的重要依据,也是影响其时间开销的最主要部分。为了减少算法时间开销,通过对现有算法FHARA的正域计算进行改进,采取保留策略,利用矩阵保留度量计算值的平方,将原本<i>n</i>维上的计算改进为1维上的计算,从而缩减了每次度量计算的时间,并在此基础上提出了基于矩阵保留策略的邻域粗糙集属性约简算法,最后通过多个UCI数据集验证了该算法。与现有算法相比较,实验结果表明,对大部分数据集而言,该算法能有效且更快速地得到数据集的属性约简。
关键词 邻域粗糙集; 正域; 属性约简; 快速算法
基金项目 国家自然科学基金资助项目(61503208)
本文URL http://www.arocmag.com/article/01-2019-12-010.html
英文标题 Neighborhood rough set attribute reduction algorithm based on matrix reservation strategy
作者英文名 Gao Yang, Liu Zunren, Ji Jun
机构英文名 College of Computer Science & Technology,Qingdao University,Qingdao Shandong 266071,China
英文摘要 For an attribute reduction algorithm based on the neighborhood rough set model, the calculation of the positive region is the necessary basis of its efficient performance and the uppermost part of its time cost. In order to reduce the time overhead of the algorithm, this paper improved the positive region calculation of the existing algorithm FHARA, adopted the reservation strategy and used the matrix to preserve the square of the calculated values. It improved the original <i>n</i>-dimensional computation to 1 dimensional computation, which reduced the computation time of each metric calculation. On this basis, it proposed a neighborhood rough set attribute reduction algorithm based on the matrix reservation strategy. Finally, the algorithm was verified by multiple UCI data sets. Compared with existing algorithms, the experimental results show that the proposed algorithm can get the attribute reduction of the dataset more effectively and quickly for most data sets.
英文关键词 neighborhood rough set; positive region; attribute reduction; fast algorithm
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收稿日期 2018/5/11
修回日期 2018/7/2
页码 3570-3573
中图分类号 TP391
文献标志码 A