• DocumentCode
    1470658
  • Title

    Feature selection via discretization

  • Author

    Liu, Huan ; Setiono, Rudy

  • Author_Institution
    Dept. of Inf. Syst. & Comput. Sci., Nat. Univ. of Singapore, Singapore
  • Volume
    9
  • Issue
    4
  • fYear
    1997
  • Firstpage
    642
  • Lastpage
    645
  • Abstract
    Discretization can turn numeric attributes into discrete ones. Feature selection can eliminate some irrelevant and/or redundant attributes. Chi2 is a simple and general algorithm that uses the χ 2 statistic to discretize numeric attributes repeatedly until some inconsistencies are found in the data. It achieves feature selection via discretization. It can handle mixed attributes, work with multiclass data, and remove irrelevant and redundant attributes
  • Keywords
    data handling; feature extraction; learning (artificial intelligence); pattern classification; Chi2; chi2 statistic; discretization; feature selection; general algorithm; inconsistencies; mixed attributes; multiclass data; numeric attributes; pattern classification; redundant attribute removal; redundant attributes; Accuracy; Classification algorithms; Computer science; Information systems; Merging; Notice of Violation; Pattern classification; Remuneration; Statistics; Training data;
  • fLanguage
    English
  • Journal_Title
    Knowledge and Data Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1041-4347
  • Type

    jour

  • DOI
    10.1109/69.617056
  • Filename
    617056
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1470658