IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v216y2014i1p191-20310.1007-s10479-012-1300-5.html
   My bibliography  Save this article

SVM classification for imbalanced data sets using a multiobjective optimization framework

Author

Listed:
  • Ayşegül Aşkan
  • Serpil Sayın

Abstract

Classification of imbalanced data sets in which negative instances outnumber the positive instances is a significant challenge. These data sets are commonly encountered in real-life problems. However, performance of well-known classifiers is limited in such cases. Various solution approaches have been proposed for the class imbalance problem using either data-level or algorithm-level modifications. Support Vector Machines (SVMs) that have a solid theoretical background also encounter a dramatic decrease in performance when the data distribution is imbalanced. In this study, we propose an L 1 -norm SVM approach that is based on a three objective optimization problem so as to incorporate into the formulation the error sums for the two classes independently. Motivated by the inherent multi objective nature of the SVMs, the solution approach utilizes a reduction into two criteria formulations and investigates the efficient frontier systematically. The results indicate that a comprehensive treatment of distinct positive and negative error levels may lead to performance improvements that have varying degrees of increased computational effort. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Ayşegül Aşkan & Serpil Sayın, 2014. "SVM classification for imbalanced data sets using a multiobjective optimization framework," Annals of Operations Research, Springer, vol. 216(1), pages 191-203, May.
    • Handle: RePEc:spr:annopr:v:216:y:2014:i:1:p:191-203:10.1007/s10479-012-1300-5
    DOI: 10.1007/s10479-012-1300-5
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10479-012-1300-5
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10479-012-1300-5?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Fruhwirth, Bernd & Mekelburg, Karsten, 1994. "On the efficient point set of tricriteria linear programs," European Journal of Operational Research, Elsevier, vol. 72(1), pages 192-199, January.
    2. Panos Kouvelis & Serpil Sayın, 2006. "Algorithm robust for the bicriteria discrete optimization problem," Annals of Operations Research, Springer, vol. 147(1), pages 71-85, October.
    3. Shuchun Wang & Wei Jiang & Kwok-Leung Tsui, 2010. "Adjusted support vector machines based on a new loss function," Annals of Operations Research, Springer, vol. 174(1), pages 83-101, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kyungsik Lee & Norman Kim & Myong Jeong, 2014. "The sparse signomial classification and regression model," Annals of Operations Research, Springer, vol. 216(1), pages 257-286, May.
    2. Klamroth, Kathrin & Köbis, Elisabeth & Schöbel, Anita & Tammer, Christiane, 2017. "A unified approach to uncertain optimization," European Journal of Operational Research, Elsevier, vol. 260(2), pages 403-420.
    3. Seyyed Amir Babak Rasmi & Ali Fattahi & Metin Türkay, 2021. "SASS: slicing with adaptive steps search method for finding the non-dominated points of tri-objective mixed-integer linear programming problems," Annals of Operations Research, Springer, vol. 296(1), pages 841-876, January.
    4. Stacey Faulkenberg & Margaret Wiecek, 2012. "Generating equidistant representations in biobjective programming," Computational Optimization and Applications, Springer, vol. 51(3), pages 1173-1210, April.
    5. Shuguang He & Wei Jiang & Houtao Deng, 2018. "A distance-based control chart for monitoring multivariate processes using support vector machines," Annals of Operations Research, Springer, vol. 263(1), pages 191-207, April.
    6. Marie Schmidt & Leo Kroon & Anita Schöbel & Paul Bouman, 2017. "The Travelers Route Choice Problem Under Uncertainty: Dominance Relations Between Strategies," Operations Research, INFORMS, vol. 65(1), pages 184-199, February.
    7. Yazan F. Roumani & Yaman Roumani & Joseph K. Nwankpa & Mohan Tanniru, 2018. "Classifying readmissions to a cardiac intensive care unit," Annals of Operations Research, Springer, vol. 263(1), pages 429-451, April.
    8. Pablo Aparicio-Ruiz & Elena Barbadilla-Martín & José Guadix & Pablo Cortés, 2021. "KNN and adaptive comfort applied in decision making for HVAC systems," Annals of Operations Research, Springer, vol. 303(1), pages 217-231, August.
    9. Alexander Engau, 2017. "Proper Efficiency and Tradeoffs in Multiple Criteria and Stochastic Optimization," Mathematics of Operations Research, INFORMS, vol. 42(1), pages 119-134, January.
    10. Jyrki Wallenius & James S. Dyer & Peter C. Fishburn & Ralph E. Steuer & Stanley Zionts & Kalyanmoy Deb, 2008. "Multiple Criteria Decision Making, Multiattribute Utility Theory: Recent Accomplishments and What Lies Ahead," Management Science, INFORMS, vol. 54(7), pages 1336-1349, July.
    11. Bérubé, Jean-François & Gendreau, Michel & Potvin, Jean-Yves, 2009. "An exact [epsilon]-constraint method for bi-objective combinatorial optimization problems: Application to the Traveling Salesman Problem with Profits," European Journal of Operational Research, Elsevier, vol. 194(1), pages 39-50, April.
    12. C. Gutiérrez & L. Huerga & E. Köbis & C. Tammer, 2021. "A scalarization scheme for binary relations with applications to set-valued and robust optimization," Journal of Global Optimization, Springer, vol. 79(1), pages 233-256, January.
    13. Hombach, Laura Elisabeth & Büsing, Christina & Walther, Grit, 2018. "Robust and sustainable supply chains under market uncertainties and different risk attitudes – A case study of the German biodiesel market," European Journal of Operational Research, Elsevier, vol. 269(1), pages 302-312.
    14. Marie Schmidt & Leo Kroon & Anita Schöbel & Paul Bouman, 2017. "The Travelers Route Choice Problem Under Uncertainty: Dominance Relations Between Strategies," Operations Research, INFORMS, vol. 65(1), pages 184-199, 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:spr:annopr:v:216:y:2014:i:1:p:191-203:10.1007/s10479-012-1300-5. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.