IDEAS home Printed from https://ideas.repec.org/a/ids/ijidsc/v4y2012i2-3p217-250.html
   My bibliography  Save this article

Exploring filter-based feature selection techniques for software quality classification

Author

Listed:
  • Kehan Gao
  • Taghi M. Khoshgoftaar
  • Huanjing Wang

Abstract

The quality of software products can be estimated and improved by building software quality classification models. The predictive accuracy of the software quality classification models is usually affected by two factors: the learning model(s) used in classification and the quality of the data. This study examined both influencing factors, but we concentrated more on the quality of the data by selecting a subset of relevant features for building classification models. We investigated four filter-based feature selection techniques in a case study on a very large telecommunications software system. The empirical results demonstrated that by applying attribute selection we can build classification models with prediction accuracy comparable to or even better than those built with a complete set of attributes, even though the smaller subset of attributes had less than 15% of the complete set of attributes.

Suggested Citation

  • Kehan Gao & Taghi M. Khoshgoftaar & Huanjing Wang, 2012. "Exploring filter-based feature selection techniques for software quality classification," International Journal of Information and Decision Sciences, Inderscience Enterprises Ltd, vol. 4(2/3), pages 217-250.
    • Handle: RePEc:ids:ijidsc:v:4:y:2012:i:2/3:p:217-250
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=47074
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ids:ijidsc:v:4:y:2012:i:2/3:p:217-250. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=306 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.