• DocumentCode
    3751992
  • Title

    Multi codebook LVQ-based artificial neural network using clustering approach

  • Author

    M. Anwar Ma´sum;H. R. Sanabila;W. Jatmiko; Aprinaldi

  • Author_Institution
    Faculty of Computer Science Universitas Indonesia
  • fYear
    2015
  • Firstpage
    263
  • Lastpage
    268
  • Abstract
    In this paper we proposed multicodebook LVQ-based artificial neural network classifier using clustering approach. The classifiers are LVQ, LVQ2-1, GLVQ, and FNGLVQ. The clustering algorithm used to build multi codebook is K-Means, IK-Means, and GMM. Experiment result shows that on synthteic dataset multi codebook FNGLVQ using GMM clustering has higest improvement with 19,53% mprovement compared to FNGLVQ. Whereas on bencmark dataset multi codebook LVQ2-1 using K-Means clustering has higest improvement with 5,83% improvement cmpared to LVQ-2.1.
  • Keywords
    "Benchmark testing","Iris","Ionosphere","Cancer"
  • Publisher
    ieee
  • Conference_Titel
    Advanced Computer Science and Information Systems (ICACSIS), 2015 International Conference on
  • Type

    conf

  • DOI
    10.1109/ICACSIS.2015.7415193
  • Filename
    7415193