Skip to main content
SpringerLink
Log in

Data Mining for Data Classification Based on the KNN-Fuzzy Method Supported by Genetic Algorithm

  • Conference paper
  • First Online:
High Performance Computing for Computational Science — VECPAR 2002 (VECPAR 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2565))

Abstract

This paper presents a classification method based on the KNN-Fuzzy classification algorithm, supported by Genetic Algorithm. It discusses how to consider data clustering according to the Fuzzy logic and its consequences in the area of Data Mining. Analyses are made upon the results obtained in the classification of several data bases in order to demonstrate the proposed theory.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. ANDERBERG, MICHAEL R. Cluster Analysis for Applications. Academic Press, 1973.

    Google Scholar 

  2. MITCHIE, D., SPIEGELHALTER, D. J., TAYLOR, C. C. Machine Learning, Neural and Statistical Classification. Ellis Horwood, 1994.

    Google Scholar 

  3. MANLY, B. F. J. Multivariate Statistical Methods. A Primer, Chapman & Hall, London, 1986.

    Google Scholar 

  4. KELLER, J. M., GRAY, M. R., GIVENS JR., J. A., A Fuzzy K-Nearest Neighbor Algorithm, IEEE Transactions on Systems, Man, and Cybernetics, v. SMC-15, n. 4, pp. 258–260, July/August 1985.

    Google Scholar 

  5. HEATH, F. G., Origins of Binary Code, Scientific American, v.227, n.2, pp.76–83, August 1972.

    Article  Google Scholar 

  6. ESPÍNDOLA, ROGÉRIO P. Optimizing Classification Fuzzy Rules by Genetic Algorithms, M.Sc thesys, COPPE/PEC, May, 1999.

    Google Scholar 

  7. KDD-Sisyphus. KDD Sisyphus Workshop—Data Preparation, Preprocessing and Reasoning for Real-World Data Mining Applications. Internet: http://research.swisslife.ch/kdd-sisyphus, 1998.

Download references

Author information

Authors and Affiliations

  1. COPPE, Universidade Federal do Rio de Janeiro, Brazil

    José L. A. Rosa & Nelson F. F. Ebecken

Authors
  1. José L. A. Rosa
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nelson F. F. Ebecken
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Faculdade de Engenharia da, Universidade do Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    José M. L. M. Palma  & A. Augusto Sousa  & 

  2. Department of Computer Science, University of Tennessee, 37996-1301, Knoxville, TN, USA

    Jack Dongarra

  3. Departamento de Sistemas Informáticos y Computación, Universidad Politécnica de Valencia, Camino de Vera, s/n, Apartado 22012, 46020, Valencia, Spain

    Vicente Hernández

Rights and permissions

Reprints and permissions

Copyright information

© 2003 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Rosa, J.L.A., Ebecken, N.F.F. (2003). Data Mining for Data Classification Based on the KNN-Fuzzy Method Supported by Genetic Algorithm. In: Palma, J.M.L.M., Sousa, A.A., Dongarra, J., Hernández, V. (eds) High Performance Computing for Computational Science — VECPAR 2002. VECPAR 2002. Lecture Notes in Computer Science, vol 2565. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36569-9_9

Download citation

  • DOI: https://doi.org/10.1007/3-540-36569-9_9

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00852-1

  • Online ISBN: 978-3-540-36569-3

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation