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Composite Rough Sets

机译:复合粗糙集

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摘要

There are multiple kinds of data in information systems, e.g., categorical data, numerical data, set-valued data, interval-valued data and missing data. Such information systems are called as composite information systems in this paper. To process such data, composite rough sets are introduced, composite relation is defined and composite classes are used to drive approximations from composite information systems. Lower and upper approximations of a concept are the basis for rule acquisition and attribute reduction in rough set theory. To intuitively compute the approximations, positive, boundary and negative regions, matrix-based method is presented in composite rough sets. A case study validates the feasibility of the proposed method.
机译:信息系统中有多种数据,例如分类数据,数值数据,设定值数据,区间值数据和缺失数据。这种信息系统在本文中称为复合信息系统。为了处理这样的数据,引入了复合粗糙集,定义了复合关系,并使用复合类来驱动来自复合信息系统的近似值。概念的上下近似是粗糙集理论中规则获取和属性约简的基础。为了直观地计算近似值,正,边界和负区域,在复合粗糙集中提出了基于矩阵的方法。案例研究验证了该方法的可行性。

著录项

  • 来源
  • 会议地点 Chengdu(CN)
  • 作者单位

    School of Information Science and Technology, Southwest Jiaotong University, Chengdu 610031, China,Department of Computer Science, Georgia State University, Atlanta, GA 30303, USA;

    School of Information Science and Technology, Southwest Jiaotong University, Chengdu 610031, China;

    School of Information Science and Technology, Southwest Jiaotong University, Chengdu 610031, China;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Composite Rough Sets; Information Systems; Matrix;

    机译:复合粗糙集;信息系统;矩阵;

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