• DocumentCode
    2785871
  • Title

    Incremental selection of the neighborhood size for ISOMAP

  • Author

    Shao, Chao

  • Author_Institution
    Sch. of Inf., Henan Univ. of Finance & Econ., Zhengzhou
  • Volume
    1
  • fYear
    2008
  • fDate
    12-15 July 2008
  • Firstpage
    436
  • Lastpage
    441
  • Abstract
    The success of ISOMAP depends greatly on selecting a suitable neighborhood size; however, itpsilas an open problem how to do this efficiently. When the neighborhood size becomes unsuitable, shortcut edges can be introduced into the neighborhood graph and destroy the approximation ability of the involved shortest-path distances to the corresponding geodesic distances greatly. Itpsilas obvious that shortcut edge links two endpoints lying close in Euclidean space but far away on the manifold, which can be measured approximately by its order presented in this paper. Based on the observation, this paper presented an efficient method to find a suitable neighborhood size incrementally, which doesn´t need to compute shortest-path distances or run the MDS algorithm as those methods based on residual variance do. Finally, the feasibility of this method can be verified by experimental results.
  • Keywords
    differential geometry; graph theory; Euclidean space; ISOMAP; MDS algorithm; approximation ability; geodesic distances; incremental neighborhood size selection; neighborhood graph; shortest-path distances; Chaos; Data visualization; Embedded computing; Euclidean distance; Explosives; Extraterrestrial measurements; Finance; Level measurement; Machine learning; Size measurement; Data visualization; ISOMAP; Neighborhood size; Order; Residual variance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2008 International Conference on
  • Conference_Location
    Kunming
  • Print_ISBN
    978-1-4244-2095-7
  • Electronic_ISBN
    978-1-4244-2096-4
  • Type

    conf

  • DOI
    10.1109/ICMLC.2008.4620445
  • Filename
    4620445