• DocumentCode
    2053285
  • Title

    An Improved Method of Outlier Detection Based on Frequent Pattern

  • Author

    Zhang, Weiwei ; Wu, Jianhua ; Yu, Jie

  • Author_Institution
    Dept. of Comput. Sci., Jinan Univ., Zhuhai, China
  • Volume
    2
  • fYear
    2010
  • fDate
    14-15 Aug. 2010
  • Firstpage
    3
  • Lastpage
    6
  • Abstract
    Outlier detection is an interesting data mining task, which detects rare events. This paper focuses on the method of outlier detection based on frequent pattern (FP method for short). First we analyze the drawback of this method, and then an improved method (LFP method for short) has been presented. Finally, we evaluate the two methods by using several datasets and the experiment results show that LFP method outperforms FP method.
  • Keywords
    data mining; LFP method; data mining; frequent pattern; outlier detection; Accuracy; Algorithm design and analysis; Complexity theory; Computer science; Data mining; Helium; Itemsets; association rules; data mining; frequent pattern; outlier detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Engineering (ICIE), 2010 WASE International Conference on
  • Conference_Location
    Beidaihe, Hebei
  • Print_ISBN
    978-1-4244-7506-3
  • Electronic_ISBN
    978-1-4244-7507-0
  • Type

    conf

  • DOI
    10.1109/ICIE.2010.97
  • Filename
    5571194
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2053285