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Computational Enhancements in Tree-Growing Methods

  • Jan Klaschka
  • Roberta Siciliano
  • Jaromír Antoch
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)

Abstract

In this paper we show how to avoid unnecessary calculations and to save considerably the computational cost in a wide class of tree-based methods. So called auxiliary statistics, which enable to restrict handling the raw data, are introduced. Aside that, a fast splitting algorithm is outlined, which allows to recognize and avoid unnecessary split evaluations during the search of an optimal split. Relationships between the computational cost savings and properties of both a specific method and data are summarized.

Key Words

Classification and regression trees computational cost auxiliary statistics fast splitting algorithm 

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References

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Copyright information

© Springer-Verlag Berlin · Heidelberg 1998

Authors and Affiliations

  • Jan Klaschka
    • 1
    • 2
    • 3
  • Roberta Siciliano
    • 1
    • 2
    • 3
  • Jaromír Antoch
    • 1
    • 2
    • 3
  1. 1.ICS CASPragueCzech Rep.
  2. 2.Univ. of NaplesNaplesItaly
  3. 3.Charles Univ.PragueCzech Rep.

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