• Title of article

    Analysis of data complexity measures for classification

  • Author/Authors

    Cano، نويسنده , , José-Ramَn، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2013
  • Pages
    12
  • From page
    4820
  • To page
    4831
  • Abstract
    The study of data complexity metrics is an emergent area in the field of data mining and is focused on the analysis of several data set characteristics to extract knowledge from them. This information can be used to support the election of the proper classification algorithm. aper addresses the analysis of the relationship between data complexity measures and classifiers behavior. Each one of the metrics is evaluated covering its range of values and studying the classifiers accuracy on these values. sults offer information about the usefullness of these measures, and which of them allow us to analyze the nature of the input data set and help us to decide which classification method could be the most promising one.
  • Keywords
    data complexity , Class overlapping , Classification , Class separability
  • Journal title
    Expert Systems with Applications
  • Serial Year
    2013
  • Journal title
    Expert Systems with Applications
  • Record number

    2353718