IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-05331339.html

Support Vector Machines

Author

Listed:
  • Yoann Pull

    (LEO - Laboratoire d'Économie d'Orleans [2022-...] - UO - Université d'Orléans - UT - Université de Tours - UCA - Université Clermont Auvergne)

Abstract

This lecture note offers a rigorous introduction to Support Vector Machines (SVMs) at the crossroads of geometry, convex optimization, and kernel methods. We review Euclidean geometry and Rosenblatt's perceptron, then develop the large-margin classifier: primal/dual formulations, KKT conditions, and the role of support vectors. Kernelization is formalized through RKHS and the representer theorem, enabling nonlinear decision boundaries. Extensions include soft-margin SVM, SVR, LS-SVM, multiclass strategies (OvR/OvO), and probability calibration (sigmoid, isotonic). The final part gathers practical modeling principles and hyperparameter tuning. The course targets Master's-level students with background in statistical learning, functional analysis, linear algebra, and optimization; technical sections and further readings are flagged throughout.

Suggested Citation

  • Yoann Pull, 2025. "Support Vector Machines," Post-Print hal-05331339, HAL.
    • Handle: RePEc:hal:journl:hal-05331339
    Note: View the original document on HAL open archive server: https://hal.science/hal-05331339v1
    as

    Download full text from publisher

    File URL: https://hal.science/hal-05331339v1/document
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:hal:journl:hal-05331339. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.