Skip to main content
SpringerLink
Log in

Knowledge Discovery from Health Data Using Weighted Aggregation Classifiers

  • Conference paper
  • First Online:
Discovery Science (DS 1999)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1721))

Included in the following conference series:

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 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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

References

  1. T. Fukuda, Y. Morimoto, S. Morishita, and T. Tokuyama. Constructing efficient decision trees by using optimized numeric association rules, In Proc. the 22th VLDB Conference, 146–155, 1996.

    Google Scholar 

  2. R. C. Holte. Very simple classification rules perform well on most commonly used datasets, Machine Learning, 11, 63–91, 1993.

    Article  MATH  Google Scholar 

  3. P. M. Murphy and D. W. Aha. UCI repository of machine learning databases, 1994. http://www.ics.uci.edu/mlearn/MLRepository.html.

    Google Scholar 

  4. J. R. Quinlan. C4.5: Programs for machine learning, Morgan Kaufmann, 1993.

    Google Scholar 

  5. The Committee for Statistics of Student Health (CSSH) in National University. The data of health condition in students of national universities, 1997.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Dept. Informatics, Kyushu Univ., Hakozaki 6-10-1, Fukuoka, 812-8581, Japan

    Toru Takae, Minoru Chikamune, Hiroki Arimura & Ayumi Shinohara

  2. Univ. Comput. Center, Kyushu Univ., Hakozaki 6-10-1, Fukuoka, 812-8581, Japan

    Hitoshi Inoue & Shun-ichi Takeya

  3. Inst. Health Science, Kyushu Univ., Kasuga-koen 6-1, Kasuga, 816-8580, Japan

    Keiko Uezono & Terukazu Kawasaki

Authors
  1. Toru Takae
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Minoru Chikamune
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hiroki Arimura
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ayumi Shinohara
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Hitoshi Inoue
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Shun-ichi Takeya
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Keiko Uezono
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Terukazu Kawasaki
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Informatics, Kyushu University, 6-10-1 Hakozaki, Higashi-ku, Fukuoka, 812-8581, Japan

    Setsuo Arikawa

  2. Graduate School of Media and Governance, Keio University, 5322 Endoh, Fujisawa-shi, Kanagawa, 252-8520, Japan

    Koichi Furukawa

Rights and permissions

Reprints and permissions

Copyright information

© 1999 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Takae, T. et al. (1999). Knowledge Discovery from Health Data Using Weighted Aggregation Classifiers. In: Arikawa, S., Furukawa, K. (eds) Discovery Science. DS 1999. Lecture Notes in Computer Science(), vol 1721. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46846-3_48

Download citation

  • DOI: https://doi.org/10.1007/3-540-46846-3_48

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66713-1

  • Online ISBN: 978-3-540-46846-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation