• DocumentCode
    3440747
  • Title

    Outlier detection using k-nearest neighbour graph

  • Author

    Hautamäki, Ville ; Kärkkäinen, Ismo ; Fränti, Pasi

  • Author_Institution
    Dept. of Comput. Sci., Joensuu Univ., Finland
  • Volume
    3
  • fYear
    2004
  • fDate
    23-26 Aug. 2004
  • Firstpage
    430
  • Abstract
    We present an outlier detection using indegree number (ODIN) algorithm that utilizes k-nearest neighbour graph. Improvements to existing kNN distance-based method are also proposed. We compare the methods with real and synthetic datasets. The results show that the proposed method achieves reasonable results with synthetic data and outperforms compared methods with real data sets with small number of observations.
  • Keywords
    graph theory; pattern clustering; distance based method; indegree number algorithm; k-nearest neighbour graph; outlier detection algorithm; Breast cancer; Cancer detection; Computer science; Computer security; Data mining; Gaussian distribution; Intrusion detection; Pattern recognition; Probability density function; Statistical distributions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-2128-2
  • Type

    conf

  • DOI
    10.1109/ICPR.2004.1334558
  • Filename
    1334558