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Application of a method of managing evidential reasoning to decision tree classifier

  • Ling Liu
  • Bao-kai He
Classifiation Techniques
Part of the Lecture Notes in Computer Science book series (LNCS, volume 301)

Abstract

The possibility and advantage of applying a method of managing evidential reasoning to decision tree classifyer is discussed. Relative algorithms are proposed and some experiments have been conducted. Results are very good.

Keywords

Feature Extraction Internal Node Tree Classifier Error Accumulation Evidential Reasoning 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [1]
    J. Pearl, "Research note on Evidential Reasoning in a Hierarchy of Hypotheses", Artifial Intelligenc AI-28, pp9–15, 1986CrossRefGoogle Scholar
  2. [2]
    Q.R. Wang and C.Y. Suen, "Analysis and Design of a Decition Tree Based on Entropy Reduction and Its Application to Large Character Set Recognition", IEEE Tr.Vol PAMI-6, pp406–417, 1984Google Scholar
  3. [3]
    M. Ben-Bassat and L. Zaidenberg, "Contextual Template Matching: A Distance Measure for Patterns with Hierarchically Dependent Features", IEEE Tr.Vol PAMI-6, pp201–211, 1984Google Scholar
  4. [4]
    Q.R. Wang and C.Y. Suen, "Large Tree Classifier with Heuristic Search and Global Training", IEEE Tr.Vol PAMI-9, pp91–103, 1987Google Scholar
  5. [5]
    A.V.Kulkarni and L.N.Kanal, "Admissible Search Strategies for Parametric and Nonparametric Hierarchical Classification", in proc. of 4th IJCPR, Japan, Nov. 1978Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1988

Authors and Affiliations

  • Ling Liu
    • 1
  • Bao-kai He
    • 1
  1. 1.Dept of Applied MathematicsChengdu College of GeologyChengduThe People's Republic of China

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