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Generation of Reducts Based on Nearest Neighbor Relations and Boolean Reasoning

机译:基于最近邻关系和布尔推理的约简生成

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Dimension reduction of data is an important issue in the data processing and it is needed for the analysis of higher dimensional data in the application domains. Rough set is fundamental and useful to reduce higher dimensional data to lower one. Reduct in the rough set is a minimal subset of features, which has the same discernible power as the entire features in the higher dimensional scheme. It is shown that nearest neighbor relation with minimal distance proposed here has a fundamental information for classification. In this paper, the nearest neighbor relation plays a fundamental role for generation of reducts using the Boolean reasoning. Then, two reduct generation methods based on the nearest neighbor relation with minimal distance are proposed here, which are derived from Boolean expression of nearest neighbor relations and their operations.
机译:数据降维是数据处理中的重要问题,在应用程序域中分析更高维度的数据时需要用到它。粗糙集对于将高维数据减少为低维数据是基本且有用的。粗糙集中的约简是特征的最小子集,与高维方案中的整个特征具有相同的可分辨能力。结果表明,本文提出的距离最小的最近邻关系具有分类的基本信息。在本文中,最近邻关系在使用布尔推理生成归约中起着基本作用。然后,本文提出了两种基于最小距离的最近邻关系的约简生成方法,它们是从最近邻关系的布尔表达式及其操作中推导而来的。

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