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Unsupervised and supervised data classification via nonsmooth and global optimization

Author

Listed:
  • A. Bagirov
  • A. Rubinov
  • N. Soukhoroukova
  • J. Yearwood

Abstract

No abstract is available for this item.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:topjnl:v:11:y:2003:i:1:p:1-75
    DOI: 10.1007/BF02578945
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    Citations

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    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    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. 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".
    11. 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.
    12. 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.
    13. 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.

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