IDEAS home Printed from https://ideas.repec.org/a/csb/stintr/v13y2012i3p569-580.html
   My bibliography  Save this article

An empirical analysis of the effectiveness of Wishart and Mojena criteria in cluster analysis

Author

Listed:
  • Artur Mikulec
  • Aleksandra Kupis-Fijałkowska

Abstract

Mojena and Wishart criteria are methods of selecting the optimal grouping result of agglomerative cluster analysis methods (hierarchical). Two criteria were proposed by Mojena in the 70’s of the 20th century: the upper tail rule and moving average quality control rule, both based on an analysis of the fusion levels of objects in the dendrogram with the aim to determine the cut-off point of it, i.e. to choose the optimal clustering result. The third criterion: tree validation was created by Wishart and evaluates the randomness of the objects clustering in the dendrogram. The purpose of this paper is to present the results of the empirical analysis of the effectiveness of Mojena and Wishart criteria for the number of clusters selection, in comparison to other applicable criteria in this area, including those proposed by: Baker and Hubert, Calinski and Harabasz, Davies and Bouldin, Hubert and Levine. The empirical analysis has been carried out in ClustanGraphics 8 Program and selected packages in R environment for the generated data sets.

Suggested Citation

  • Artur Mikulec & Aleksandra Kupis-Fijałkowska, 2012. "An empirical analysis of the effectiveness of Wishart and Mojena criteria in cluster analysis," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 13(3), pages 569-580, December.
    • Handle: RePEc:csb:stintr:v:13:y:2012:i:3:p:569-580
    as

    Download full text from publisher

    File URL: http://index.stat.gov.pl/repec/files/csb/stintr/csb_stintr_v13_2012_i3_n9.pdf
    Download Restriction: no
    ---><---

    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:csb:stintr:v:13:y:2012:i:3:p:569-580. 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: Beata Witek (email available below). General contact details of provider: https://edirc.repec.org/data/gusgvpl.html .

    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.