• DocumentCode
    3617474
  • Title

    Energy generalized LVQ with relevance factors

  • Author

    A. Cataron;R. Andonie

  • Author_Institution
    Dept. of Electron. & Comput., Transylvania Univ. of Brasov, Romania
  • Volume
    2
  • fYear
    2004
  • fDate
    6/26/1905 12:00:00 AM
  • Firstpage
    1421
  • Abstract
    Input feature ranking and selection represent a necessary preprocessing stage in classification, especially when one is required to manage large quantities of data. We introduce a weighted generalized LVQ algorithm, called energy generalized relevance LVQ (EGRLVQ), based on the Onicescu´s informational energy. EGRLVQ is an incremental learning algorithm for supervised classification and feature ranking.
  • Keywords
    "Clustering algorithms","Prototypes","Euclidean distance","Computer science","Vector quantization","Bayesian methods","Training data","Iterative algorithms","Convergence","Data structures"
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-8359-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.2004.1380159
  • Filename
    1380159
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3617474