Skip to main content
SpringerLink
Log in
Book cover

International Conference on Computational Collective Intelligence

ICCCI 2016: Computational Collective Intelligence pp 451–461Cite as

Intersection Method, Union Method, Product Rule and Weighted Average Method in a Dispersed Decision-Making System - a Comparative Study on Medical Data

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9876))

Abstract

In this article a dispersed decision-making system, that was proposed in the previous paper of one of the authors, is used. In the system four selected fusion methods were used. The aim of the paper is to compare the efficiency of inference of these methods for knowledge base from the medical field. Two medical data sets from the UC Irvine Machine Learning Repository were used. Note that these databases were used in a dispersed form, which means that one knowledge base was transformed into a set of knowledge bases. This application was intended to reflect a situation in which many medical centers independently collect knowledge from one field and then we want to use all of this knowledge at the same time in the process of inference.

This is a preview of subscription content, 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 EPUB and 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

Learn about institutional subscriptions

References

  1. Fumera, G., Roli, F.: Performance analysis and comparison of linear combiners for classifier fusion. In: Proceeding of 16th International Conference on Pattern Recognition, Canada (2002)

    Google Scholar 

  2. Gatnar, E.: Multiple-model approach to classification and regression. PWN, Warsaw (2008). (in Polish)

    Google Scholar 

  3. Ho, T.K., Hull, J.J., Srihari, S.N.: Decision combination in multiple classifier systems. IEEE Trans. Pattern Anal. Mach. Intell. 16(1), 66–75 (1994)

    Article  Google Scholar 

  4. Kittler, J., Hatef, M., Duin, R.P.W., Matas, J.: On combining classifiers. IEEE Trans. Pattern Anal. Mach. Intell. 20(3), 226–239 (1998)

    Article  Google Scholar 

  5. Kuncheva, L., Bezdek, J.C., Duin, R.P.W.: Decision templates for multiple classifier fusion: an experimental comparison. Pattern Recogn. 34(2), 299–314 (2001)

    Article  MATH  Google Scholar 

  6. Kuncheva, L.: Combining Pattern Classifiers Methods and Algorithms. Wiley, Chichester (2004)

    Book  MATH  Google Scholar 

  7. Littlestone, N., Warmuth, M.: The weighted majority algorithm. Inf. Comput. 108(2), 212–261 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  8. Nowak-Brzezińska, A., Rybotycki, T.: Visualization of medical rule-based knowledge bases. J. Med. Inform. Technol. 24, 91–98 (2015)

    Google Scholar 

  9. Nowak-Brzezińska, A., Wakulicz-Deja, A.: Exploration of Knowledge bases inspired by rough set theory. In: Proceedings of the 24th International Workshop on Concurrency, Specification and Programming, pp. 64–75 (2015)

    Google Scholar 

  10. Przybyła-Kasperek, M., Wakulicz-Deja, A.: Application of reduction of the set of conditional attributes in the process of global decision-making. Fund. Inform. 122(4), 327–355 (2013)

    MathSciNet  MATH  Google Scholar 

  11. Przybyła-Kasperek, M., Wakulicz-Deja, A.: Global decision-making system with dynamically generated clusters. Inf. Sci. 270, 172–191 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  12. Przybyła-Kasperek, M., Wakulicz-Deja, A.: A dispersed decision-making system - The use of negotiations during the dynamic generation of a systems structure. Inf. Sci. 288, 194–219 (2014)

    Article  MATH  Google Scholar 

  13. Przybyła-Kasperek, M., Wakulicz-Deja, A.: Global decision-making in multi-agent decision-making system with dynamically generated disjoint clusters. Appl. Soft Comput. 40, 603–615 (2016)

    Article  MATH  Google Scholar 

  14. Przybyła-Kasperek, M., Wakulicz-Deja, A.: The strength of coalition in a dispersed decision support system with negotiations. Eur. J. Oper. Res. 252(3), 947–968 (2016). http://dx.doi.org/10.1016/j.ejor.2016.02.008

    Article  MathSciNet  MATH  Google Scholar 

  15. Simiński, R., Nowak-Brzezińska, A.: Goal-driven inference for web knowledge based system. In: Wilimowska, Z., Borzemski, L., Grzech, A., Swiatek, J. (eds.) ISAT 2015. AISC, vol. 432, pp. 99–109. Springer, Switzerland (2015)

    Google Scholar 

  16. Wakulicz-Deja, A., Przybyła-Kasperek, M.: Application of the method of editing and condensing in the process of global decision-making. Fund. Inform. 106(1), 93–117 (2011)

    MathSciNet  MATH  Google Scholar 

  17. Xu, L., Krzyzak, A., Suen, C.Y.: Methods of combining multiple classifiers and their application to handwriting recognition. IEEE Trans. Syst. Man Cybern. 22, 418–435 (1992)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Computer Science, University of Silesia, Bȩdzińska 39, 41-200, Sosnowiec, Poland

    Małgorzata Przybyła-Kasperek & Agnieszka Nowak-Brzezińska

Authors
  1. Małgorzata Przybyła-Kasperek
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Agnieszka Nowak-Brzezińska
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Małgorzata Przybyła-Kasperek .

Editor information

Editors and Affiliations

  1. Wroclaw University of Technology , Wroclaw, Poland

    Ngoc Thanh Nguyen

  2. Aristotle University of Thessaloniki , Thessaloniki, Greece

    Lazaros Iliadis

  3. Department of Forestry and Manageme, Democritus University of Thrace Department of Forestry and Manageme, Orestiada Thrace, Greece

    Yannis Manolopoulos

  4. Wrocław University of Technology , Wrocław, Poland

    Bogdan Trawiński

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Przybyła-Kasperek, M., Nowak-Brzezińska, A. (2016). Intersection Method, Union Method, Product Rule and Weighted Average Method in a Dispersed Decision-Making System - a Comparative Study on Medical Data. In: Nguyen, N., Iliadis, L., Manolopoulos, Y., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2016. Lecture Notes in Computer Science(), vol 9876. Springer, Cham. https://doi.org/10.1007/978-3-319-45246-3_43

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-45246-3_43

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-45245-6

  • Online ISBN: 978-3-319-45246-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation