From Research on Modeling of Uncertain Data: The Case of Small and Medium Enterprises

  • A. Burda
  • Z. S. Hippe
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 98)

Abstract

A new procedure for combined validation of learning models – built for specifically uncertain data – is briefly described. The procedure, called the queue validation, relies on a combination of resubstitution with the modified learn-and-test paradigm. In the initial experiment [Burda and Hippe 2010] the developed procedure was checked on doubtful (presumably distorted by creative accounting) data, related to small and medium enterprises (further called SME), displaying two concepts: bankrupt or non-bankrupt. In the current research a new set of learning models was generated for the same data using various types of optimized artificial neural networks. All learning models were evaluated using the queue validation methodology. It was found that error rates for bankrupt concept are much larger than error rates for the concept non-bankrupt. It is assumed that this difference in error rates discovered by thequeue validation procedure can be probably used as a hint pointing frauds in the investigated SME data.

Keywords

Artificial Neural Network Radial Basis Function Learning Model Radial Basis Function Network Uncertain Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [Burda 2009]
    Burda, A.: Multicategory evaluation of prediction models for small and medium enterprises. Barometr Regionalny 15, 77–84 (2009)Google Scholar
  2. [Burda and Hippe 2010]
    Burda, A., Hippe, Z.S.: Uncertain data modeling: The case of small and medium enterprises. In: Pardela, T., Wilamowski, B. (eds.) 3rd International Conference on Human System Interaction, pp. 76–80. e-Book, Rzeszów (2010)CrossRefGoogle Scholar
  3. [Haider and Bukhari 2007]
    Haider, S.A., Bukhari, A.S.: Evaluating Financial sector firm’s creditworthiness for south-asian countries. Asian Journal of Information Technology 6, 329–341 (2007)Google Scholar
  4. [Hippe 1999]
    Hippe, Z.S.: Data mining and knowledge discovery in business: past, present, and future. In: Abramowicz, W., Orłowska, M. (eds.) Business Information Systems 1999, pp. 158–169. Springer, Heidelberg (1999)Google Scholar
  5. [Hippe and Knap 2003]
    Hippe, Z.S., Knap, M.: Research on development of certainand possible decision trees. In: Krawczyk, H., Kubale, M. (eds.) Informational Technologies, pp. 189–194. Gdańsk Univ. Edit. Office, Gdańsk (2003)Google Scholar
  6. [Kim and Sohn 2010]
    Kim, H.S., Sohn, S.Y.: Support vector machines for default prediction of SMEs based on technology credit. European Journal of Operational Research 201, 838–846 (2010)MATHCrossRefGoogle Scholar
  7. [Nowak 1998]
    Nowak, M.: Practical evaluation of the enterprise financial condition, p. 89. Foundation of Accountancy Development in Poland, Warsaw (1998)Google Scholar
  8. [Pongsatat et al. 2004]
    Pongsatat, S., Ramage, J., Lawrence, H.: Bankruptcy prediction for large and small firms in asia: A comparison of ohlson and altman. Journal of Accounting and Corporate Governance 2, 1–13 (2004)Google Scholar
  9. [Powell 2001]
    Powell, M.J.D.: Radial basis function methods for interpolation to functions in many variables. Report DAMPT 2001/NA11, Department of Applied Mathematics and Theoretical Physics, University of Cambridge (2001)Google Scholar
  10. [Rumelhart and McClelland 1986]
    Rumelhart, D.E., McClelland, J. (eds.): Parallel distributed processing, 1st edn. MIT Press, Cambridge (1986)Google Scholar
  11. [Schmiemann 2008]
    Schmiemann, M.: Enterprises by size class-overview of SMEs in the EU (2008), epp.-eurostat.ec.europa.eu/cache/ITY_OFFPUB/KS-SF-08-031/EN/KS-SF-08-031-EN.PDF (accessed January 20, 2011)

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • A. Burda
    • 1
  • Z. S. Hippe
    • 2
  1. 1.University of Management and AdministrationZamośćPoland
  2. 2.Institute of Biomedical InformaticsUniversity of Information Technology and ManagementRzeszówPoland

Personalised recommendations