Skip to main content
SpringerLink
Log in
SpringerLink
Log in

Two Methods of Combining Classifiers, Which are Based on Decision Templates and Theory of Evidence, in a Dispersed Decision-Making System

  • Conference paper
  • First Online:
Beyond Databases, Architectures and Structures. Advanced Technologies for Data Mining and Knowledge Discovery (BDAS 2015, BDAS 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 613))

Abstract

Issues that are related to decision making that is based on dispersed knowledge are discussed in the paper. The main aim of the paper is to compare the results obtained using two different methods of conflict analysis in a dispersed decision-making system. The conflict analysis methods, used in the article, are discussed in the paper of Kuncheva et al. [5] and in the paper of Rogova [16]. These methods are used if the individual classifiers generate vectors that represent the probability distributions over different decision. Both methods belong to the class-indifferent group, i.e. methods that use all of decision profile matrices to calculate the support for each class. Also, both methods require training. These methods were used in a dispersed decision-making system which was proposed in the paper [12].

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 EPUB and 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

References

  1. http://mlr.cs.umass.edu/ml/datasets.html

  2. Bregar, A.: Towards a framework for the measurement and reduction of user-perceivable complexity of group decision-making methods. IJDSST 6(2), 21–45 (2014)

    Google Scholar 

  3. Gatnar, E.: Multiple-Model Approach to Classification and Regression. PWN, Warsaw (2008)

    Google Scholar 

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

    Book  MATH  Google Scholar 

  5. Kuncheva, L.I., 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. Matsatsinis, N., Samaras, A.P.: MCDA and preference disaggregation in group decision support systems. EJOR 130(2), 414–429 (2001)

    Article  MATH  Google Scholar 

  7. Pawlak, Z.: On conflicts. Int. J. Man-Mach. Stud. 21(2), 127–134 (1984)

    Article  MATH  Google Scholar 

  8. Pawlak, Z.: Rough Sets: Theoretical Aspects of Reasoning about Data. Kluwer, Dordrecht (1991)

    Book  MATH  Google Scholar 

  9. Pawlak, Z.: An inquiry into anatomy of conflicts. Inf. Sci. 109(1–4), 65–78 (1998)

    Article  MathSciNet  Google Scholar 

  10. Przybyła-Kasperek, M.: Selected methods of combining classifiers, when predictions are stored in probability vectors, in a dispersed decision-making system. In: 24th International Workshop, CS&P, pp. 211–222 (2015)

    Google Scholar 

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

    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 system’s structure. Inf. Sci. 288, 194–219 (2014)

    Article  Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  14. Przybyła-Kasperek, M.: Global decisions taking process, including the stage of negotiation, on the basis of dispersed medical data. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B., Kostrzewa, D. (eds.) BDAS 2014. CCIS, vol. 424, pp. 290–299. Springer, Heidelberg (2014)

    Google Scholar 

  15. Przybyła-Kasperek, M.: Application of the Shapley-Shubik power index in the process of decision making on the basis of dispersed medical data. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B., Kostrzewa, D. (eds.) BDAS 2015. CCIS, vol. 521, pp. 277–287. Springer, Heidelberg (2015)

    Google Scholar 

  16. Rogova, G.L.: Combining the results of several neural network classifiers. Neural Netw. 7(5), 777–781 (1994)

    Article  Google Scholar 

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

    MathSciNet  MATH  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

Authors
  1. Małgorzata Przybyła-Kasperek
    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. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Stanisław Kozielski

  2. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Dariusz Mrozek

  3. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Paweł Kasprowski

  4. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Bożena Małysiak-Mrozek

  5. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Daniel Kostrzewa

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Przybyła-Kasperek, M. (2016). Two Methods of Combining Classifiers, Which are Based on Decision Templates and Theory of Evidence, in a Dispersed Decision-Making System. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B., Kostrzewa, D. (eds) Beyond Databases, Architectures and Structures. Advanced Technologies for Data Mining and Knowledge Discovery. BDAS BDAS 2015 2016. Communications in Computer and Information Science, vol 613. Springer, Cham. https://doi.org/10.1007/978-3-319-34099-9_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-34099-9_7

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-34098-2

  • Online ISBN: 978-3-319-34099-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation