• DocumentCode
    519600
  • Title

    A classification method based on PAM algorithm and discrete preprocess

  • Author

    Yang, Huaizhen ; Li, Lei

  • Author_Institution
    Sch. of Bus., Guilin Univ. of Electron. Technol., Guilin, China
  • Volume
    2
  • fYear
    2010
  • fDate
    21-24 May 2010
  • Abstract
    Using clustering method to generate training set, and applying rough set theory to discretization preprocess, the classification accuracy can be improve well. This paper applied PAM clustering algorithm to constitute a training set from original sample, used a discrete algorithm that integrates Boolean logic with rough set theory to discretize the training set, and trained classifier by the discrete training set. When classification was carried out in the same data set, experimental results showed that compared to the RDDTE method only based on the PAM algorithm to preprocess, the classification accuracy based on the new method increased 15.5 percentage points at most. Besides, the new method selected a smaller amount of training set.
  • Keywords
    Boolean functions; pattern classification; pattern clustering; rough set theory; Boolean logic; PAM clustering algorithm; classification method; discrete preprocess; discrete training set; rough set theory; Boolean functions; Clustering algorithms; Clustering methods; Decision trees; Information systems; Information technology; Machine learning algorithms; Production; Set theory; Training data; PAM; cross validation; data discretization; heuristic algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Future Computer and Communication (ICFCC), 2010 2nd International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-5821-9
  • Type

    conf

  • DOI
    10.1109/ICFCC.2010.5497346
  • Filename
    5497346