• DocumentCode
    2752214
  • Title

    Gradual fuzzy decision trees to help medical diagnosis

  • Author

    Marsala, Christophe

  • Author_Institution
    LIP6, Univ. Pierre et Marie Curie, Paris, France
  • fYear
    2012
  • fDate
    10-15 June 2012
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In this paper, we consider the problem of the construction of fuzzy decision trees when there exists a graduality between the values of attributes and values of the class. We propose a new measure, extended from the measure of classification ambiguity, that takes into account both discrimination power and graduality with regards to the class. To highlight the importance of that kinds of measures, Medical applications is presented in which often the values of the class are symbolic and ordered and in which the discovery of gradual links between descriptive attributes and the class are seek for.
  • Keywords
    decision trees; fuzzy set theory; learning (artificial intelligence); medical computing; patient diagnosis; pattern classification; classification ambiguity; discrimination power; gradual fuzzy decision trees; medical applications; medical diagnosis; Biomedical equipment; Decision trees; Entropy; Indexes; Medical services; Power measurement; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems (FUZZ-IEEE), 2012 IEEE International Conference on
  • Conference_Location
    Brisbane, QLD
  • ISSN
    1098-7584
  • Print_ISBN
    978-1-4673-1507-4
  • Electronic_ISBN
    1098-7584
  • Type

    conf

  • DOI
    10.1109/FUZZ-IEEE.2012.6251147
  • Filename
    6251147