• DocumentCode
    3180083
  • Title

    An advanced cluster analysis method based on statistical test

  • Author

    Gao, Xinbo ; Ji, Hongbing ; Li, Jie

  • Author_Institution
    Sch. of Electron. Eng., Xidian Univ., Xi´´an, China
  • Volume
    2
  • fYear
    2002
  • fDate
    26-30 Aug. 2002
  • Firstpage
    1100
  • Abstract
    The paper presents a novel clustering algorithm supervised by statistical tests. It deals simultaneously with three key data analysis problems: cluster tendency; cluster analysis; cluster validity. It provides an effective tool to analyze the validity and reasonableness of unsupervised pattern classification, especially in the case of a large number of samples. The experimental result illustrates its effectiveness.
  • Keywords
    pattern classification; pattern clustering; set theory; statistical analysis; cluster analysis method; cluster tendency; cluster validity; clustering algorithm; multi-variable statistical analysis; pattern clustering; statistical test; unlabelled pattern set; unsupervised classification; unsupervised pattern classification; Clustering algorithms; Data analysis; Density functional theory; Electronic equipment testing; Partitioning algorithms; Pattern analysis; Pattern clustering; Pattern recognition; Performance analysis; Statistical analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing, 2002 6th International Conference on
  • Print_ISBN
    0-7803-7488-6
  • Type

    conf

  • DOI
    10.1109/ICOSP.2002.1179981
  • Filename
    1179981