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A Practicable Heuristic Attributes Reduction Algorithm for Ordered Information Systems

机译:一种有序信息系统的实用启发式属性约简算法

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摘要

Rough set theory is a mathematic tool to handlevague and uncertain knowledge. The core problem of rough set theory is the reduction of attributes. This paperintroduces apresentation of the information granularity for ordered information systems based on dominance relation, and detail the way to calculate the attribute importance based on the information granularity we have defined. On that basis, put forward a heuristic attribute reduction algorithm for ordered information systems. Experiments show that the algorithm performs well and outperforms some other rivals.
机译:粗糙集理论是处理模糊和不确定知识的数学工具。粗糙集理论的核心问题是属性的约简。本文介绍了基于优势关系的有序信息系统的信息粒度表示,并详细介绍了基于我们定义的信息粒度计算属性重要性的方法。在此基础上,提出了有序信息系统的启发式属性约简算法。实验表明,该算法性能良好,性能优于其他竞争对手。

著录项

  • 来源
    《Foundations of intelligent systems》|2011年|p.141-149|共9页
  • 会议地点 Shanghai(CN);Shanghai(CN)
  • 作者

    Wei Li; Feng Liu; Zhi-hong Zhao;

  • 作者单位

    Supported by the Fundamental Research Funds for the Central Universities(1118021707) Software Institute, Nanjing University, Nanjing, Jiangsu Province, 210093, China;

    Supported by the Fundamental Research Funds for the Central Universities(1118021707) Software Institute, Nanjing University, Nanjing, Jiangsu Province, 210093, China;

    Supported by the Fundamental Research Funds for the Central Universities(1118021707) Software Institute, Nanjing University, Nanjing, Jiangsu Province, 210093, China;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 人工智能理论;
  • 关键词

    rough set theory; dominance relationships; attributes reduction; information granularity;

    机译:粗糙集理论;优势关系;属性减少;信息粒度;

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