• DocumentCode
    314345
  • Title

    Fast inner-outer point evaluation in a polytopic generalization domain

  • Author

    Agamennoni, Osvaldo ; Mandolesi, Pablo S.

  • Author_Institution
    Dept. de Ingenieria Electrica, Univ. Nacional del Sur, Bahia Blanca, Argentina
  • Volume
    3
  • fYear
    1997
  • fDate
    9-12 Jun 1997
  • Firstpage
    1547
  • Abstract
    In this paper the generalization domain or applicability domain of a given model is addressed. The generalization domain is related with the interpolation domain that is usually defined through the polytope formed by the training data. Some considerations about the relationship between the interpolation and the generalization domains are given. A fast algorithm to test in real time if a model input is inside or outside the interpolation domain is presented. This is a more general problem commonly encountered in many areas, i.e., to check if a point is inside or not a given polytope. An example to evaluate points of a sphere from a closed ball is discussed to show the performance of the algorithm
  • Keywords
    computational geometry; feedforward neural nets; generalisation (artificial intelligence); interpolation; optimisation; real-time systems; feedforward neural network; inner-outer point evaluation; interpolation; polytope; polytopic generalization domain; real time systems; Clustering algorithms; Density functional theory; Electronic mail; Extrapolation; Interpolation; Neural networks; Partitioning algorithms; Recurrent neural networks; Testing; Training data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks,1997., International Conference on
  • Conference_Location
    Houston, TX
  • Print_ISBN
    0-7803-4122-8
  • Type

    conf

  • DOI
    10.1109/ICNN.1997.614123
  • Filename
    614123