IDEAS home Printed from https://ideas.repec.org/a/spr/jclass/v42y2025i2d10.1007_s00357-024-09499-7.html
   My bibliography  Save this article

A Storage and Classification Algorithm for Concept Drift Data Streams Based on OS-ELM

Author

Listed:
  • Ying Mei

    (Lishui University
    Zhejiang Detu Network Co., Ltd.)

  • Chengbo Lu

    (Lishui University
    Zhejiang Detu Network Co., Ltd.)

  • Chenghao Tang

    (Hangzhou Steam Turbine Co., Ltd.)

  • Yonghua Wu

    (Zhejiang Sci-Tech University)

  • Guoqing Meng

    (Zhejiang Sci-Tech University)

Abstract

Many methods can deal with some special cases of data streams (e.g., concept drift) currently; however, these methods need to store historical data and access them repeatedly, which is inconsistent with the single-channel characteristics of data streams, and it requires a large amount of memory space to save data when very slow gradual drift occurs due to the infinite feature of data streams. To address this problem, this paper proposes a concept drift data stream storage and classification algorithm based on OS-ELM (SC-OS-ELM), which uses a matrix of fixed size to save the feature information of historical data, and retrains the classifier by accessing this feature matrix when needed. It achieves the goal of improving the classification accuracy while storing the feature information of historical data in a small and constant memory space. It can help algorithms such as the DDM to solve the data storage problem, making it more applicable. Comparative experimental results on 15 artificial and real data streams validate the effectiveness of SC-OS-ELM, with a significant reduction in the amount of memory space required.

Suggested Citation

  • Ying Mei & Chengbo Lu & Chenghao Tang & Yonghua Wu & Guoqing Meng, 2025. "A Storage and Classification Algorithm for Concept Drift Data Streams Based on OS-ELM," Journal of Classification, Springer;The Classification Society, vol. 42(2), pages 414-434, July.
    • Handle: RePEc:spr:jclass:v:42:y:2025:i:2:d:10.1007_s00357-024-09499-7
    DOI: 10.1007/s00357-024-09499-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00357-024-09499-7
    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/s00357-024-09499-7?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

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:spr:jclass:v:42:y:2025:i:2:d:10.1007_s00357-024-09499-7. 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: 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.