IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/8906034.html
   My bibliography  Save this article

Two-Stage Bagging Pruning for Reducing the Ensemble Size and Improving the Classification Performance

Author

Listed:
  • Hua Zhang
  • Yujie Song
  • Bo Jiang
  • Bi Chen
  • Guogen Shan

Abstract

Ensemble methods, such as the traditional bagging algorithm, can usually improve the performance of a single classifier. However, they usually require large storage space as well as relatively time-consuming predictions. Many approaches were developed to reduce the ensemble size and improve the classification performance by pruning the traditional bagging algorithms. In this article, we proposed a two-stage strategy to prune the traditional bagging algorithm by combining two simple approaches: accuracy-based pruning (AP) and distance-based pruning (DP). These two methods, as well as their two combinations, “AP+DP” and “DP+AP” as the two-stage pruning strategy, were all examined. Comparing with the single pruning methods, we found that the two-stage pruning methods can furthermore reduce the ensemble size and improve the classification. “AP+DP” method generally performs better than the “DP+AP” method when using four base classifiers: decision tree, Gaussian naive Bayes, K-nearest neighbor, and logistic regression. Moreover, as compared to the traditional bagging, the two-stage method “AP+DP” improved the classification accuracy by 0.88%, 4.06%, 1.26%, and 0.96%, respectively, averaged over 28 datasets under the four base classifiers. It was also observed that “AP+DP” outperformed other three existing algorithms Brag, Nice, and TB assessed on 8 common datasets. In summary, the proposed two-stage pruning methods are simple and promising approaches, which can both reduce the ensemble size and improve the classification accuracy.

Suggested Citation

  • Hua Zhang & Yujie Song & Bo Jiang & Bi Chen & Guogen Shan, 2019. "Two-Stage Bagging Pruning for Reducing the Ensemble Size and Improving the Classification Performance," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-17, January.
  • Handle: RePEc:hin:jnlmpe:8906034
    DOI: 10.1155/2019/8906034
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2019/8906034.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/MPE/2019/8906034.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2019/8906034?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
    ---><---

    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:hin:jnlmpe:8906034. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.