• DocumentCode
    2763596
  • Title

    Minimum Attribute Number in Decision Table Based on Maximum Entropy Principle

  • Author

    Dong, Min ; Jiang, HuiYu

  • Volume
    2
  • fYear
    2010
  • fDate
    6-7 March 2010
  • Firstpage
    446
  • Lastpage
    448
  • Abstract
    Decision tables are always extremely important objects in data mining. People often require the more simple decision table in order to reduce the scale of tables. But a decision table is not always the most simple, so we have to try reducting it to learn which condition attributes are essential. It is known that the reduct results are not usually unique and the cardinal numbers of condition attributes set in different deducted tables of the same tables are different. From research findings on reducted tables, however, we can find out a simplest condition attributes set and call it Minimum Attribute Set. According to information theory, in this paper, we have deduced a formula to calculate the cardinal number of the Minimum Attribute Set, which is called Minimum Attribute Number. Moreover, before reducted we can just know whether the table is the simplest one or not. Eventually, we give a simple test example.
  • Keywords
    Chemical engineering; Data engineering; Data mining; Educational institutions; Entropy; Information systems; Information theory; Power engineering and energy; Set theory; Testing; Decision Table; Maximum Entropy Principle; Minimum Attribute number; reduct;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Challenges in Environmental Science and Computer Engineering (CESCE), 2010 International Conference on
  • Conference_Location
    Wuhan, China
  • Print_ISBN
    978-0-7695-3972-0
  • Electronic_ISBN
    978-1-4244-5924-7
  • Type

    conf

  • DOI
    10.1109/CESCE.2010.140
  • Filename
    5493323