KNOWLEDGE DISCOVERY METHOD IN EXPLORATORY DATA ANALYSIS

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  • Oyama Mayumi
    Information Processing Research Center, Kwansei Gakuin University
  • Okada Takashi
    Information Processing Research Center, Kwansei Gakuin University
  • Li Yongsun
    Institute of System Engineering, Jin Lin University
  • Li Guifeng
    Information Processing Research Center, Kwansei Gakuin University

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  • 知識発見法による探索的データ解析
  • チシキ ハッケンホウ ニヨル タンサクテキ データ カイセキ

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A knowledge discovery method is useful to describe the data structure using some rules, defined by the functional relationship among variables, in exploratory data analysis. In this paper, two knowledge discovery softwares, IDIS and Datalogic/R, were applied to clinical data on circulatory disease and structure activity relationship data on antiviral agent for investigating the efficiency and the performance of these methods. As a result, we found that the riles, induced by the methods, were efficient to describe the structure of the data. By changing the condition (parameters) of the methods, we can get several nunber of rules and knowledge which imply the flexible interpretations. This will be inpotant point for exploratory data analysis.

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