IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v173y2006i3p849-865.html
   My bibliography  Save this article

Classes and clusters in data analysis

Author

Listed:
  • Rubinov, A.M.
  • Soukhorokova, N.V.
  • Ugon, J.

Abstract

No abstract is available for this item.

Suggested Citation

  • Rubinov, A.M. & Soukhorokova, N.V. & Ugon, J., 2006. "Classes and clusters in data analysis," European Journal of Operational Research, Elsevier, vol. 173(3), pages 849-865, September.
  • Handle: RePEc:eee:ejores:v:173:y:2006:i:3:p:849-865
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(05)00686-7
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. A.M. Bagirov & A.M. Rubinov, 2000. "Global Minimization of Increasing Positively Homogeneous Functions over the Unit Simplex," Annals of Operations Research, Springer, vol. 98(1), pages 171-187, December.
    2. A. Bagirov & A. Rubinov & N. Soukhoroukova & J. Yearwood, 2003. "Unsupervised and supervised data classification via nonsmooth and global optimization," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 11(1), pages 1-75, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hanna Górska-Warsewicz & Krystyna Rejman & Joanna Kaczorowska & Wacław Laskowski, 2021. "Vegetables, Potatoes and Their Products as Sources of Energy and Nutrients to the Average Diet in Poland," IJERPH, MDPI, vol. 18(6), pages 1-23, March.

    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. Karmitsa, Napsu & Bagirov, Adil M. & Taheri, Sona, 2017. "New diagonal bundle method for clustering problems in large data sets," European Journal of Operational Research, Elsevier, vol. 263(2), pages 367-379.
    2. A. Auslender & A. Ferrer & M. Goberna & M. López, 2015. "Comparative study of RPSALG algorithm for convex semi-infinite programming," Computational Optimization and Applications, Springer, vol. 60(1), pages 59-87, January.
    3. Adil Bagirov, 2009. "Comments on: Optimization and data mining in medicine," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 17(2), pages 250-252, December.
    4. Adil Bagirov & Asef Ganjehlou, 2008. "An approximate subgradient algorithm for unconstrained nonsmooth, nonconvex optimization," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 67(2), pages 187-206, April.
    5. Xeniya Vladimirovna Grigor’eva, 2016. "Approximate Functions in a Problem of Sets Separation," Journal of Optimization Theory and Applications, Springer, vol. 171(2), pages 550-572, November.
    6. Freitas, Paulo S.A. & Rodrigues, Antonio J.L., 2006. "Model combination in neural-based forecasting," European Journal of Operational Research, Elsevier, vol. 173(3), pages 801-814, September.
    7. Albert Ferrer & Adil Bagirov & Gleb Beliakov, 2015. "Solving DC programs using the cutting angle method," Journal of Global Optimization, Springer, vol. 61(1), pages 71-89, January.
    8. A. Bagirov & B. Ordin & G. Ozturk & A. Xavier, 2015. "An incremental clustering algorithm based on hyperbolic smoothing," Computational Optimization and Applications, Springer, vol. 61(1), pages 219-241, May.
    9. Laura Palagi, 2019. "Global optimization issues in deep network regression: an overview," Journal of Global Optimization, Springer, vol. 73(2), pages 239-277, February.
    10. Bagirov, Adil M. & Ugon, Julien & Mirzayeva, Hijran, 2013. "Nonsmooth nonconvex optimization approach to clusterwise linear regression problems," European Journal of Operational Research, Elsevier, vol. 229(1), pages 132-142.
    11. de Klerk, E. & den Hertog, D. & Elfadul, G.E.E., 2005. "On the Complexity of Optimization over the Standard Simplex," Other publications TiSEM 3789955a-6533-4a4e-aca2-6, Tilburg University, School of Economics and Management.
    12. Laura Palagi, 2017. "Global Optimization issues in Supervised Learning. An overview," DIAG Technical Reports 2017-11, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".
    13. de Klerk, E. & den Hertog, D. & Elabwabi, G., 2008. "On the complexity of optimization over the standard simplex," European Journal of Operational Research, Elsevier, vol. 191(3), pages 773-785, December.
    14. Fei Ye & Xin Yuan Lou & Lin Fu Sun, 2017. "An improved chaotic fruit fly optimization based on a mutation strategy for simultaneous feature selection and parameter optimization for SVM and its applications," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-36, April.
    15. Ghandar, Adam & Michalewicz, Zbigniew & Zurbruegg, Ralf, 2016. "The relationship between model complexity and forecasting performance for computer intelligence optimization in finance," International Journal of Forecasting, Elsevier, vol. 32(3), pages 598-613.
    16. A. M. Bagirov & B. Karasözen & M. Sezer, 2008. "Discrete Gradient Method: Derivative-Free Method for Nonsmooth Optimization," Journal of Optimization Theory and Applications, Springer, vol. 137(2), pages 317-334, May.
    17. Y. B. Zhao & D. Li, 2006. "On KKT Points of Homogeneous Programs," Journal of Optimization Theory and Applications, Springer, vol. 130(2), pages 369-376, August.
    18. A. Ferrer & M. A. Goberna & E. González-Gutiérrez & M. I. Todorov, 2017. "A comparative note on the relaxation algorithms for the linear semi-infinite feasibility problem," Annals of Operations Research, Springer, vol. 258(2), pages 587-612, November.

    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:eee:ejores:v:173:y:2006:i:3:p:849-865. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.