IDEAS home Printed from https://ideas.repec.org/a/bla/istatr/v68y2000i3p295-310.html
   My bibliography  Save this article

Ten More Years of Error Rate Research

Author

Listed:
  • Rosa A. Schiavo
  • David J. Hand

Abstract

The assessment of the performance of supervised classification rules by estimating their error rate (the proportion of objects misclassified) is an important area of work in statistical pattern recognition. This paper reviews the last ten years of error rate research, bringing up to date the reviews of Hand (1986a) and McLachlan (1987). Since those surveys were published, old estimators have been improved new estimators have been introduced, and new approaches to error rate estimation have been developed. Some of this work has led to deep insights into classification methodology and statistical modelling in general.

Suggested Citation

  • Rosa A. Schiavo & David J. Hand, 2000. "Ten More Years of Error Rate Research," International Statistical Review, International Statistical Institute, vol. 68(3), pages 295-310, December.
    • Handle: RePEc:bla:istatr:v:68:y:2000:i:3:p:295-310
    DOI: 10.1111/j.1751-5823.2000.tb00332.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1751-5823.2000.tb00332.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1751-5823.2000.tb00332.x?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
    ---><---

    Citations

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


    Cited by:

    1. Dean Fantazzini & Yufeng Xiao, 2023. "Detecting Pump-and-Dumps with Crypto-Assets: Dealing with Imbalanced Datasets and Insiders’ Anticipated Purchases," Econometrics, MDPI, vol. 11(3), pages 1-73, August.
    2. Artem Sokolov & Daniel E Carlin & Evan O Paull & Robert Baertsch & Joshua M Stuart, 2016. "Pathway-Based Genomics Prediction using Generalized Elastic Net," PLOS Computational Biology, Public Library of Science, vol. 12(3), pages 1-23, March.
    3. Kim, Ji-Hyun, 2009. "Estimating classification error rate: Repeated cross-validation, repeated hold-out and bootstrap," Computational Statistics & Data Analysis, Elsevier, vol. 53(11), pages 3735-3745, September.
    4. Airola, Antti & Pahikkala, Tapio & Waegeman, Willem & De Baets, Bernard & Salakoski, Tapio, 2011. "An experimental comparison of cross-validation techniques for estimating the area under the ROC curve," Computational Statistics & Data Analysis, Elsevier, vol. 55(4), pages 1828-1844, April.
    5. Conde David & Salvador Bonifacio & Rueda Cristina & Fernández Miguel A., 2013. "Performance and estimation of the true error rate of classification rules built with additional information. An application to a cancer trial," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 12(5), pages 583-602, October.

    More about this item

    Statistics

    Access and download statistics

    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:bla:istatr:v:68:y:2000:i:3:p:295-310. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/isiiinl.html .

    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.