IDEAS home Printed from https://ideas.repec.org/a/jss/jstsof/v017i02.html
   My bibliography  Save this article

ada: An R Package for Stochastic Boosting

Author

Listed:
  • Culp, Mark
  • Johnson, Kjell
  • Michailides, George

Abstract

Boosting is an iterative algorithm that combines simple classification rules with "mediocre" performance in terms of misclassification error rate to produce a highly accurate classification rule. Stochastic gradient boosting provides an enhancement which incorporates a random mechanism at each boosting step showing an improvement in performance and speed in generating the ensemble. ada is an R package that implements three popular variants of boosting, together with a version of stochastic gradient boosting. In addition, useful plots for data analytic purposes are provided along with an extension to the multi-class case. The algorithms are illustrated with synthetic and real data sets.

Suggested Citation

  • Culp, Mark & Johnson, Kjell & Michailides, George, 2006. "ada: An R Package for Stochastic Boosting," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 17(i02).
    • Handle: RePEc:jss:jstsof:v:017:i02
    DOI: http://hdl.handle.net/10.18637/jss.v017.i02
    as

    Download full text from publisher

    File URL: https://www.jstatsoft.org/index.php/jss/article/view/v017i02/v17i02.pdf
    Download Restriction: no
    File URL: https://www.jstatsoft.org/index.php/jss/article/downloadSuppFile/v017i02/ada_2.0-1.tar.gz
    Download Restriction: no
    File URL: https://www.jstatsoft.org/index.php/jss/article/downloadSuppFile/v017i02/v17i02.R.zip
    Download Restriction: no
    File URL: https://libkey.io/http://hdl.handle.net/10.18637/jss.v017.i02?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. Matthias Bogaert & Michel Ballings & Martijn Hosten & Dirk Van den Poel, 2017. "Identifying Soccer Players on Facebook Through Predictive Analytics," Decision Analysis, INFORMS, vol. 14(4), pages 274-297, December.
    2. Dominik P. Heinisch & Guido Buenstorf, 2018. "The next generation (plus one): an analysis of doctoral students’ academic fecundity based on a novel approach to advisor identification," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 351-380, October.
    3. Ying-Qi Zhao & Michael R. Kosorok, 2014. "Discussion of combining biomarkers to optimize patient treatment recommendations," Biometrics, The International Biometric Society, vol. 70(3), pages 713-716, September.
    4. Alfaro, Esteban & Gamez, Matias & García, Noelia, 2013. "adabag: An R Package for Classification with Boosting and Bagging," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 54(i02).
    5. Heinisch, Dominik & König, Johannes & Otto, Anne, 2019. "The IAB-INCHER project of earned doctorates (IIPED): A supervised machine learning approach to identify doctorate recipients in the German integrated employment biography data," IAB-Discussion Paper 201913, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    6. Adler, Werner & Lausen, Berthold, 2009. "Bootstrap estimated true and false positive rates and ROC curve," Computational Statistics & Data Analysis, Elsevier, vol. 53(3), pages 718-729, January.

    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:jss:jstsof:v:017:i02. 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: Christopher F. Baum (email available below). General contact details of provider: http://www.jstatsoft.org/ .

    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.