• DocumentCode
    2770301
  • Title

    Probabilistic NeuroScale for Uncertainty Visualisation

  • Author

    Sivaraksa, Mingmanas ; Lowe, David

  • Author_Institution
    Neural Comput. Res. Group, Aston Univ., Birmingham, UK
  • fYear
    2009
  • fDate
    15-17 July 2009
  • Firstpage
    74
  • Lastpage
    79
  • Abstract
    This paper is a study of low dimensional visualisation methods for data visualisation under uncertainty of the input data. It focuses on NeuroScale, the feed-forward neural networks algorithm by trying to make the algorithm able to accommodate the uncertainty. The standard model is shown not to work well under high levels of noise within the data and need to be modified. The modifications of the model are verified by using synthetic data to show their ability to accommodate the noise.
  • Keywords
    data visualisation; feedforward neural nets; probability; data visualisation; feed-forward neural networks algorithm; probabilistic neuroscale; uncertainty visualisation; Biological neural networks; Data analysis; Data visualization; Euclidean distance; Feedforward neural networks; Feedforward systems; Level measurement; Neural networks; Noise level; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Visualisation, 2009 13th International Conference
  • Conference_Location
    Barcelona
  • ISSN
    1550-6037
  • Print_ISBN
    978-0-7695-3733-7
  • Type

    conf

  • DOI
    10.1109/IV.2009.106
  • Filename
    5190865
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2770301