• Title of article

    General framework for class-specific feature selection

  • Author/Authors

    Pineda-Bautista، نويسنده , , B?rbara B. and Carrasco-Ochoa، نويسنده , , J.A. and Mart??nez-Trinidad، نويسنده , , J. Fco.، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2011
  • Pages
    7
  • From page
    10018
  • To page
    10024
  • Abstract
    Commonly, when a feature selection algorithm is applied, a single feature subset is selected for all the classes, but this subset could be inadequate for some classes. Class-specific feature selection allows selecting a possible different feature subset for each class. However, all the class-specific feature selection algorithms have been proposed for a particular classifier, which reduce their applicability. In this paper, a general framework for using any traditional feature selector for doing class-specific feature selection, which allows using any classifier, is proposed. Experimental results and a comparison against traditional feature selectors showing the suitability of the proposed framework are included.
  • Keywords
    Supervised classification , Classifier ensemble , Class-specific feature selection , feature selection
  • Journal title
    Expert Systems with Applications
  • Serial Year
    2011
  • Journal title
    Expert Systems with Applications
  • Record number

    2349825