IDEAS home Printed from https://ideas.repec.org/a/wsi/ijitdm/v21y2022i06ns0219622022500328.html
   My bibliography  Save this article

A New Approach to Correspondence Analysis Based on Interval-Valued Hesitant Fuzzy Sets

Author

Listed:
  • Ozgur Yanmaz

    (Department of Industrial Engineering, Istanbul Technical University, Macka Istanbul 34367, Turkey)

  • Cigdem Kadaifci

    (Department of Industrial Engineering, Istanbul Technical University, Macka Istanbul 34367, Turkey)

  • Erhan Bozdag

    (Department of Industrial Engineering, Istanbul Technical University, Macka Istanbul 34367, Turkey)

Abstract

Correspondence Analysis (CA), a multivariate statistical technique, allows a visual representation of the association between categorical variables through a contingency table consisting of frequencies representing the existence of relationships. Despite being a widely used statistical technique, the classical CA is not able to demonstrate the uncertainty in real-life problems. To address this issue, a new Interval-valued Hesitant Fuzzy CA approach is proposed to represent the uncertainty caused by human doubt. Due to the nature of operations defined on Hesitant Fuzzy Sets, it is hard to integrate the fuzzy calculations directly into the classical CA. Thus, a new hesitant expected value method is proposed to reveal the independence between two categorical variables. As the output of the proposed approach, an interval-valued hesitant fuzzy correspondence map consisting of rectangles of different sizes representing the amount of the hesitancy is constructed. The applicability of the proposed approach is demonstrated by a simple but effective illustrative example.

Suggested Citation

  • Ozgur Yanmaz & Cigdem Kadaifci & Erhan Bozdag, 2022. "A New Approach to Correspondence Analysis Based on Interval-Valued Hesitant Fuzzy Sets," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 21(06), pages 1749-1776, December.
  • Handle: RePEc:wsi:ijitdm:v:21:y:2022:i:06:n:s0219622022500328
    DOI: 10.1142/S0219622022500328
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0219622022500328
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://libkey.io/10.1142/S0219622022500328?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.

    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:wsi:ijitdm:v:21:y:2022:i:06:n:s0219622022500328. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/ijitdm/ijitdm.shtml .

    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.