• DocumentCode
    2681596
  • Title

    Adapting Fuzzy Points for Very-Imbalanced Datasets

  • Author

    Soler, Vicenç ; Roig, Jordi ; Prim, Marta

  • Author_Institution
    Dept. of MiSE, Univ. Autonoma of Barcelona, Bellaterra
  • fYear
    2006
  • fDate
    3-6 June 2006
  • Firstpage
    211
  • Lastpage
    216
  • Abstract
    RecBF networks come from RBF Networks, and are composed by a set of fuzzy points which describe the network. How to adapt these fuzzy points to work with very imbalanced datasets is described in this paper. Once the fuzzy points are found and adapted by the modifications proposed, they are included in a fuzzy system that classifies imbalanced datasets. The results showed will proof empirically that the proposed changes work well for very-imbalanced datasets
  • Keywords
    database theory; fuzzy set theory; radial basis function networks; RBF networks; fuzzy points; fuzzy system; imbalanced datasets; Chromium; Data mining; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Input variables; Neurons; Radial basis function networks; Strontium; Training data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Information Processing Society, 2006. NAFIPS 2006. Annual meeting of the North American
  • Conference_Location
    Montreal, Que.
  • Print_ISBN
    1-4244-0362-6
  • Electronic_ISBN
    1-4244-0363-4
  • Type

    conf

  • DOI
    10.1109/NAFIPS.2006.365410
  • Filename
    4216803
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2681596