IDEAS home Printed from https://ideas.repec.org/a/eee/jmvana/v98y2007i4p695-705.html
   My bibliography  Save this article

A penalized criterion for variable selection in classification

Author

Listed:
  • Mary-Huard, Tristan
  • Robin, Stéphane
  • Daudin, Jean-Jacques

Abstract

In this paper, the problem of variable selection in classification is considered. On the basis of recent developments in model selection theory, we provide a criterion based on penalized empirical risk, where the penalization explicitly takes into account the number of variables of the considered models. Moreover, we give an oracle-type inequality that non-asymptotically guarantees the performance of the resulting classification rule. We discuss the optimality of the proposed criterion and present an application of the main result to backward and forward selection procedures.

Suggested Citation

  • Mary-Huard, Tristan & Robin, Stéphane & Daudin, Jean-Jacques, 2007. "A penalized criterion for variable selection in classification," Journal of Multivariate Analysis, Elsevier, vol. 98(4), pages 695-705, April.
  • Handle: RePEc:eee:jmvana:v:98:y:2007:i:4:p:695-705
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0047-259X(06)00092-3
    Download Restriction: Full text for ScienceDirect subscribers only

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

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Maugis, C. & Celeux, G. & Martin-Magniette, M.-L., 2011. "Variable selection in model-based discriminant analysis," Journal of Multivariate Analysis, Elsevier, vol. 102(10), pages 1374-1387, November.

    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:eee:jmvana:v:98:y:2007:i:4:p:695-705. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.