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Using Rough Set to Induce More Abstract Rules from Rule Base

  • Feng Honghai
  • Liu Baoyan
  • He LiYun
  • Yang Bingru
  • Li Yueli
  • Zhao Shuo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4251)

Abstract

In fault diagnosis and medical diagnosis fields, often there is more than one fault or disease that occur together. In order to obtain the factors that cause a single fault to change to multi-faults, the standard rough set based methods should be rebuilt. In this paper, we propose a decernibilty matrix based algorithm with which the cause of every single fault to change to multi-faults can be revealed. Additionally, we propose another rough set based algorithm to induce the common causes of all the single faults to change to their corresponding multi-faults, which is a process of knowledge discovery in rule base, i.e., not the usual database. Inducing more abstract rules in knowledge base is a very challenging problem that has not been resolved well.

Keywords

Fault Diagnosis Decision Table Single Fault Severe Acute Respiratory Syndrome Abstract Rule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Feng Honghai
    • 1
    • 2
  • Liu Baoyan
    • 3
  • He LiYun
    • 3
  • Yang Bingru
    • 2
  • Li Yueli
    • 4
  • Zhao Shuo
    • 4
  1. 1.Urban & Rural Construction SchoolHebei Agricultural UniversityBaodingChina
  2. 2.University of Science and Technology BeijingBeijingChina
  3. 3.China Academy of Traditional Chinese MedicineBeijingChina
  4. 4.Hebei Agricultural UniversityBaodingChina

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