Integrated Model — A Proposal to handle noise

  • JoÃo Pedro Guerreiro Neto
  • Fernando José Gomes Moura Pires
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 992)


We present the theoretical background of the Integrated Model, a new induction algorithm proposed and implemented by the authors. The algorithm relies on a bottom-up strategy, from particular to general, feature less common that the usual top-down strategy founded in a great number of induction tools. We introduce a method for finding the values of the basic probability assignment according to Theory of Evidence, called probabilistic mass. With this notion, we propose a generalisation of the algorithm capable of handle noisy data.


classification rules decision trees generalization induction machine learning noise theory of evidence uncertainty measures 


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Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • JoÃo Pedro Guerreiro Neto
    • 1
  • Fernando José Gomes Moura Pires
    • 1
  1. 1.Dept. InformáticaFCT-UNL, Quinta da TorreMonte da CaparicaPortugal

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