IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0255174.html
   My bibliography  Save this article

The utility of clusters and a Hungarian clustering algorithm

Author

Listed:
  • Alfred Kume
  • Stephen G Walker

Abstract

Implicit in the k–means algorithm is a way to assign a value, or utility, to a cluster of points. It works by taking the centroid of the points and the value of the cluster is the sum of distances from the centroid to each point in the cluster. The aim in this paper is to introduce an alternative way to assign a value to a cluster. Motivation is provided. Moreover, whereas the k–means algorithm does not have a natural way to determine k if it is unknown, we can use our method of evaluating a cluster to find good clusters in a sequential manner. The idea uses optimizations over permutations and clusters are set by the cyclic groups; generated by the Hungarian algorithm.

Suggested Citation

  • Alfred Kume & Stephen G Walker, 2021. "The utility of clusters and a Hungarian clustering algorithm," PLOS ONE, Public Library of Science, vol. 16(8), pages 1-23, August.
    • Handle: RePEc:plo:pone00:0255174
    DOI: 10.1371/journal.pone.0255174
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0255174
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0255174&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0255174?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
    ---><---

    References listed on IDEAS

    as
    1. Mayra Z Rodriguez & Cesar H Comin & Dalcimar Casanova & Odemir M Bruno & Diego R Amancio & Luciano da F Costa & Francisco A Rodrigues, 2019. "Clustering algorithms: A comparative approach," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-34, January.
    2. Patrick K. Kimes & Yufeng Liu & David Neil Hayes & James Stephen Marron, 2017. "Statistical significance for hierarchical clustering," Biometrics, The International Biometric Society, vol. 73(3), pages 811-821, September.
    3. Robert Thorndike, 1953. "Who belongs in the family?," Psychometrika, Springer;The Psychometric Society, vol. 18(4), pages 267-276, December.
    4. Robert Tibshirani & Guenther Walther & Trevor Hastie, 2001. "Estimating the number of clusters in a data set via the gap statistic," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(2), pages 411-423.
    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. Dario Cottafava & Giulia Sonetti & Paolo Gambino & Andrea Tartaglino, 2018. "Explorative Multidimensional Analysis for Energy Efficiency: DataViz versus Clustering Algorithms," Energies, MDPI, vol. 11(5), pages 1-18, May.
    2. Ebba Mark & Ryan Rafaty & Moritz Schwarz, 2022. "Spatial-temporal dynamics of employment shocks in declining coal mining regions and potentialities of the 'just transition'," Papers 2211.12619, arXiv.org.
    3. Arévalo, Franklim & Barucca, Paolo & Téllez-León, Isela-Elizabeth & Rodríguez, William & Gage, Gerardo & Morales, Raúl, 2022. "Identifying clusters of anomalous payments in the salvadorian payment system," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 3(1).
    4. Isakov , Alexander, 2013. "Stress indicator construction for internal money market," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 30(2), pages 77-92.
    5. Simon Crase & Suresh N Thennadil, 2022. "An analysis framework for clustering algorithm selection with applications to spectroscopy," PLOS ONE, Public Library of Science, vol. 17(3), pages 1-24, March.
    6. Mr. Emre Alper & Michal Miktus, 2019. "Digital Connectivity in sub-Saharan Africa: A Comparative Perspective," IMF Working Papers 2019/210, International Monetary Fund.
    7. Gokturk Poyrazoglu, 2021. "Determination of Price Zones during Transition from Uniform to Zonal Electricity Market: A Case Study for Turkey," Energies, MDPI, vol. 14(4), pages 1-13, February.
    8. Teichgraeber, Holger & Brandt, Adam R., 2022. "Time-series aggregation for the optimization of energy systems: Goals, challenges, approaches, and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    9. Tomislava Pavić Kramarić & Mirjana Pejić Bach & Ksenija Dumičić & Berislav Žmuk & Maja Mihelja Žaja, 2018. "Exploratory study of insurance companies in selected post-transition countries: non-hierarchical cluster analysis," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(3), pages 783-807, September.
    10. Rodolfo Metulini & Giorgio Gnecco & Francesco Biancalani & Massimo Riccaboni, 2023. "Hierarchical clustering and matrix completion for the reconstruction of world input–output tables," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(3), pages 575-620, September.
    11. Douglas Steinley, 2007. "Validating Clusters with the Lower Bound for Sum-of-Squares Error," Psychometrika, Springer;The Psychometric Society, vol. 72(1), pages 93-106, March.
    12. Lucas Czech & Alexandros Stamatakis, 2019. "Scalable methods for analyzing and visualizing phylogenetic placement of metagenomic samples," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-50, May.
    13. Divinus Oppong-Tawiah & Jane Webster, 2023. "Corporate Sustainability Communication as ‘Fake News’: Firms’ Greenwashing on Twitter," Sustainability, MDPI, vol. 15(8), pages 1-26, April.
    14. Koecklin, Manuel Tong & Longoria, Genaro & Fitiwi, Desta Z. & DeCarolis, Joseph F. & Curtis, John, 2021. "Public acceptance of renewable electricity generation and transmission network developments: Insights from Ireland," Energy Policy, Elsevier, vol. 151(C).
    15. Thiemo Fetzer & Samuel Marden, 2017. "Take What You Can: Property Rights, Contestability and Conflict," Economic Journal, Royal Economic Society, vol. 0(601), pages 757-783, May.
    16. Daniel Agness & Travis Baseler & Sylvain Chassang & Pascaline Dupas & Erik Snowberg, 2022. "Valuing the Time of the Self-Employed," CESifo Working Paper Series 9567, CESifo.
    17. Batool, Fatima & Hennig, Christian, 2021. "Clustering with the Average Silhouette Width," Computational Statistics & Data Analysis, Elsevier, vol. 158(C).
    18. Nicoleta Serban & Huijing Jiang, 2012. "Multilevel Functional Clustering Analysis," Biometrics, The International Biometric Society, vol. 68(3), pages 805-814, September.
    19. Egashira, Kento & Yata, Kazuyoshi & Aoshima, Makoto, 2024. "Asymptotic properties of hierarchical clustering in high-dimensional settings," Journal of Multivariate Analysis, Elsevier, vol. 199(C).
    20. Becken, Susanne & Stantic, Bela & Chen, Jinyan & Connolly, Rod M., 2022. "Twitter conversations reveal issue salience of aviation in the broader context of climate change," Journal of Air Transport Management, Elsevier, vol. 98(C).

    More about this item

    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:plo:pone00:0255174. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.