Incremental Fuzzy Decision Trees

  • Marina Guetova
  • Steffen Hölldobler
  • Hans-Peter Störr
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2479)


We present a new classification algorithm that combines three properties: It generates decision trees, which proved a valuable and intelligible tool for classification and generalization of data; it utilizes fuzzy logic, that provides for a fine grained description of classified items adequate for human reasoning; and it is incremental, allowing rapid alternation of classification and learning of new data. The algorithm generalizes known non-incremental algorithms for top down induction of fuzzy decision trees, as well as known incremental algorithms for induction of decision trees in classical logic. The algorithm is shown to be terminating and to yield results equivalent to the non-incremental version.


incremental learning classification decision trees fuzzy logic 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Marina Guetova
    • 1
  • Steffen Hölldobler
    • 1
  • Hans-Peter Störr
    • 1
  1. 1.Artificial Intelligence Institute Department of Computer ScienceTechnische Universität DresdenDresdenGermany

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