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Rough Sets and Their Applications in Data Mining

  • Jue Wang
Chapter
Part of the The International Series on Asian Studies in Computer and Information Science book series (ASIS, volume 6)

Abstract

The main goal of data mining is to mine knowledge from large scale of datasets. And the key requirement of data mining is concise representation, which is consistent with the notion of minimal reduction in Rough Sets. This paper will regard RS as such a tool to implement the key requirement. First, we will introduce the basic problem in rough set theory — attribute reduction. Second, data enriching for UCI repository is analyzed with the measures called Evaporation Rate of Attribute, Object and Data respectively. Third, a rule+exception model is given to explain the set of learning data. Finally, some more complicated problems are discussed and the conclusions are given.

Keywords

Data mining rough sets attribute reduction data enriching rule+exception model 

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Copyright information

© Springer Science+Business Media New York 1999

Authors and Affiliations

  • Jue Wang
    • 1
  1. 1.Institute of Automation Chinese Academy of SciencesBeijingChina

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