IDEAS home Printed from https://ideas.repec.org/a/spr/fuzinf/v1y2009i2d10.1007_s12543-009-0012-2.html
   My bibliography  Save this article

A survey of fuzzy decision tree classifier

Author

Listed:
  • Yi-lai Chen

    (Nanjing Army Command College)

  • Tao Wang

    (Nanjing Army Command College)

  • Ben-sheng Wang

    (Nanjing Army Command College)

  • Zhou-jun Li

    (Beihang University)

Abstract

Decision-tree algorithm provides one of the most popular methodologies for symbolic knowledge acquisition. The resulting knowledge, a symbolic decision tree along with a simple inference mechanism, has been praised for comprehensibility. The most comprehensible decision trees have been designed for perfect symbolic data. Over the years, additional methodologies have been investigated and proposed to deal with continuous or multi-valued data, and with missing or noisy features. Recently, with the growing popularity of fuzzy representation, some researchers have proposed to utilize fuzzy representation in decision trees to deal with similar situations. This paper presents a survey of current methods for Fuzzy Decision Tree (FDT) designment and the various existing issues. After considering potential advantages of FDT classifiers over traditional decision tree classifiers, we discuss the subjects of FDT including attribute selection criteria, inference for decision assignment and stopping criteria. To be best of our knowledge, this is the first overview of fuzzy decision tree classifier.

Suggested Citation

  • Yi-lai Chen & Tao Wang & Ben-sheng Wang & Zhou-jun Li, 2009. "A survey of fuzzy decision tree classifier," Fuzzy Information and Engineering, Springer, vol. 1(2), pages 149-159, June.
    • Handle: RePEc:spr:fuzinf:v:1:y:2009:i:2:d:10.1007_s12543-009-0012-2
    DOI: 10.1007/s12543-009-0012-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12543-009-0012-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12543-009-0012-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:fuzinf:v:1:y:2009:i:2:d:10.1007_s12543-009-0012-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.