• DocumentCode
    3060994
  • Title

    Column Pruning Beats Stratification in Effort Estimation

  • Author

    Jalali, Omid ; Menzies, Tim ; Baker, Dan ; Hihn, Jairus

  • Author_Institution
    West Virginia Univ., Morgantown
  • fYear
    2007
  • fDate
    20-26 May 2007
  • Firstpage
    7
  • Lastpage
    7
  • Abstract
    Local calibration combined with stratification, also known as row pruning, is a common technique used by cost estimation professionals to improve model performance. The results presented in this paper raise several serious questions concerning the benefits of row pruning for improving effort estimation indicating the need to rethink standard practice. Firstly, the mean size of improvements from row pruning appears to be relatively small compared to the size of the standard deviations in effort estimation data. Secondly, the advantages of row pruning especially for the purposes of deleting spurious outliers can be achieved using column pruning much more effectively. Hence, we advise against row pruning and advocate column pruning instead.
  • Keywords
    estimation theory; software cost estimation; software development management; column pruning; cost estimation; effort estimation; row pruning; Calibration; Costs; Laboratories; Management training; NASA; Predictive models; Propulsion; Resource management; Training data; US Government;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Predictor Models in Software Engineering, 2007. PROMISE'07: ICSE Workshops 2007. International Workshop on
  • Conference_Location
    Minneapolis, MN
  • Print_ISBN
    0-7695-2954-2
  • Type

    conf

  • DOI
    10.1109/PROMISE.2007.3
  • Filename
    4273263