IDEAS home Printed from https://ideas.repec.org/a/spr/compst/v17y2002i2d10.1007_s001800200101.html
   My bibliography  Save this article

The Use of a Distance Measure in Regularised Discriminant Analysis

Author

Listed:
  • J. P. Koolaard

    (Crop and Food Research Limited)

  • S. Ganesalingam

    (Massey University)

  • C. R. O. Lawoko

    (National Australia Bank)

Abstract

Summary Friedman (1989) proposed a regularised discriminant function (RDF) as a compromise between the normal-based linear and quadratic discriminant functions, by considering alternatives to the usual maximum likelihood estimates for the covariance matrices. These alternatives are characterised by two (regularisation) parameters, the values of which are customised to individual situations by jointly minimising a sample-based (cross-validated) estimate of future misclassification risk. This technique appears to provide considerable gains in classification accuracy in many circumstances, although it is computationally intensive. Because of the computational burden inherent in the RDF, and with regards to criticisms of the technique by Rayens et al. (1991), we investigated whether information about appropriate values of the two regularisation parameters could be obtained from examining the behaviour of the Bhattacharyya distance between the various populations. This distance measure is found to give information which leads to unique and generally appropriate values for the regularisation parameters being selected.

Suggested Citation

  • J. P. Koolaard & S. Ganesalingam & C. R. O. Lawoko, 2002. "The Use of a Distance Measure in Regularised Discriminant Analysis," Computational Statistics, Springer, vol. 17(2), pages 185-202, July.
    • Handle: RePEc:spr:compst:v:17:y:2002:i:2:d:10.1007_s001800200101
    DOI: 10.1007/s001800200101
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s001800200101
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s001800200101?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

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

    References listed on IDEAS

    as
    1. Rayens, William & Greene, Tom, 1991. "Covariance pooling and stabilization for classification," Computational Statistics & Data Analysis, Elsevier, vol. 11(1), pages 17-42, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Raudys, Sarunas & Young, Dean M., 2004. "Results in statistical discriminant analysis: a review of the former Soviet Union literature," Journal of Multivariate Analysis, Elsevier, vol. 89(1), pages 1-35, April.
    2. Mkhadri, A. & Celeux, G. & Nasroallah, A., 1997. "Regularization in discriminant analysis: an overview," Computational Statistics & Data Analysis, Elsevier, vol. 23(3), pages 403-423, January.
    3. Yushu Liu & William Rayens, 2007. "PLS and dimension reduction for classification," Computational Statistics, Springer, vol. 22(2), pages 189-208, July.

    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:spr:compst:v:17:y:2002:i:2:d:10.1007_s001800200101. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.