IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v36y1997i1p43-47.html
   My bibliography  Save this article

A consistent combined classification rule

Author

Listed:
  • Mojirsheibani, M.

Abstract

In this article we propose a data-based method for constructing combined classifiers. The resulting classifiers, which are linear in nature, turn out to be consistent.

Suggested Citation

  • Mojirsheibani, M., 1997. "A consistent combined classification rule," Statistics & Probability Letters, Elsevier, vol. 36(1), pages 43-47, November.
    • Handle: RePEc:eee:stapro:v:36:y:1997:i:1:p:43-47
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-7152(97)00047-3
    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. Hothorn, Torsten & Lausen, Berthold, 2005. "Bundling classifiers by bagging trees," Computational Statistics & Data Analysis, Elsevier, vol. 49(4), pages 1068-1078, June.
    2. Mojirsheibani, Majid, 2002. "An Almost Surely Optimal Combined Classification Rule," Journal of Multivariate Analysis, Elsevier, vol. 81(1), pages 28-46, April.
    3. Mojirsheibani, Majid, 2000. "A kernel-based combined classification rule," Statistics & Probability Letters, Elsevier, vol. 48(4), pages 411-419, July.
    4. Esteve, Miriam & Aparicio, Juan & Rodriguez-Sala, Jesus J. & Zhu, Joe, 2023. "Random Forests and the measurement of super-efficiency in the context of Free Disposal Hull," European Journal of Operational Research, Elsevier, vol. 304(2), pages 729-744.
    5. Narayanaswamy Balakrishnan & Majid Mojirsheibani, 2015. "A simple method for combining estimates to improve the overall error rates in classification," Computational Statistics, Springer, vol. 30(4), pages 1033-1049, December.
    6. Richard A. Berk, 2006. "An Introduction to Ensemble Methods for Data Analysis," Sociological Methods & Research, , vol. 34(3), pages 263-295, February.

    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:stapro:v:36:y:1997:i:1:p:43-47. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    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.