Skip to main content
SpringerLink
Log in

On Dataset Complexity for Case Base Maintenance

  • Conference paper
Case-Based Reasoning Research and Development (ICCBR 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6880))

Included in the following conference series:

Abstract

We present what is, to the best of our knowledge, the first analysis that uses dataset complexity measures to evaluate case base editing algorithms. We select three different complexity measures and use them to evaluate eight case base editing algorithms. While we might expect the complexity of a case base to decrease, or stay the same, and the classification accuracy to increase, or stay the same, after maintenance, we find many counter-examples. In particular, we find that the RENN noise reduction algorithm may be over-simplifying class boundaries.

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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Brighton, H., Mellish, C.: On the consistency of information filters for lazy learning algorithms. In: Rauch, J., Żytkow, J.M. (eds.) PKDD 1999. LNCS (LNAI), vol. 1704, pp. 283–288. Springer, Heidelberg (1999)

    Chapter  Google Scholar 

  2. Cummins, L.: Combining and Choosing Case Base Maintenance Algorithms. PhD thesis, Department of Computer Science, University College Cork, Ireland (forthcoming, 2011)

    Google Scholar 

  3. Cummins, L., Bridge, D.: Maintenance by a committee of experts: The MACE approach to case-base maintenance. In: McGinty, L., Wilson, D.C. (eds.) ICCBR 2009. LNCS, vol. 5650, pp. 120–134. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  4. Delany, S.J.: The good, the bad and the incorrectly classified: Profiling cases for case-base editing. In: McGinty, L., Wilson, D.C. (eds.) ICCBR 2009. LNCS, vol. 5650, pp. 135–149. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  5. Delany, S.J., Cunningham, P.: An analysis of case-based editing in a spam filtering system. In: Funk, P., González Calero, P.A. (eds.) ECCBR 2004. LNCS (LNAI), vol. 3155, pp. 128–141. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  6. Doyle, D., Cunningham, P., Bridge, D., Rahman, Y.: Explanation oriented retrieval. In: Funk, P., González Calero, P.A. (eds.) ECCBR 2004. LNCS (LNAI), vol. 3155, pp. 157–168. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  7. Fornells, A., Recio-García, J.A., Díaz-Agudo, B., Golobardes, E., Fornells, E.: Integration of a methodology for cluster-based retreval in jcolibri. In: McGinty, L., Wilson, D.C. (eds.) ICCBR 2009. LNCS, vol. 5650, pp. 418–433. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  8. Frank, A., Asuncion, A.: UCI machine learning repository (2010)

    Google Scholar 

  9. Ho, T.K., Basu, M.: Measuring the complexity of classification problems. In: Procs. of the 15th Intl. Conference on Pattern Recognition, pp. 43–47 (2000)

    Google Scholar 

  10. Ho, T.K., Basu, M.: Complexity measures of supervised classification problems. IEEE Trans. on Pattern Analysis and Machine Intelligence 24(3), 289–300 (2002)

    Article  Google Scholar 

  11. Macià, N., Bernadó-Mansilla, E., Orriols-Puig, A.: On the dimensions of data complexity through synthetic data sets. In: Procs. of the 11th Intl. Conference of the Catalan Association for Artificial Intelligence, pp. 244–252 (2008)

    Google Scholar 

  12. Massie, S., Craw, S., Wiratunga, N.: Complexity profiling for informed case-base editing. In: Roth-Berghofer, T.R., Göker, M.H., Güvenir, H.A. (eds.) ECCBR 2006. LNCS (LNAI), vol. 4106, pp. 325–339. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  13. McKenna, E., Smyth, B.: Competence-guided case-base editing techniques. In: Blanzieri, E., Portinale, L. (eds.) EWCBR 2000. LNCS (LNAI), vol. 1898, pp. 186–197. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  14. Orriols-Puig, A., Macià, N., Bernadó-Mansilla, E., Ho, T.K.: Documentation for the data complexity library in C++. Technical Report GRSI Report No. 2009001, Universitat Ramon Llull (2009)

    Google Scholar 

  15. Pranckeviciene, E., Ho, T.K., Somorjai, R.: Class separability in spaces reduced by feature selection. In: Procs. of the 18th Intl. Conference on Pattern Recognition, pp. 254–257 (2006)

    Google Scholar 

  16. Smyth, B., McKenna, E.: Modelling the competence of case-bases. In: Smyth, B., Cunningham, P. (eds.) EWCBR 1998. LNCS (LNAI), vol. 1488, pp. 208–220. Springer, Heidelberg (1998)

    Chapter  Google Scholar 

  17. Tomek, I.: An experiment with the edited nearest-neighbor rule. IEEE Trans. on Systems, Man, and Cybernetics 6(6), 448–452 (1976)

    MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science, University College Cork, Ireland

    Lisa Cummins & Derek Bridge

Authors
  1. Lisa Cummins
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Derek Bridge
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Ashwin Ram Nirmalie Wiratunga

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Cummins, L., Bridge, D. (2011). On Dataset Complexity for Case Base Maintenance. In: Ram, A., Wiratunga, N. (eds) Case-Based Reasoning Research and Development. ICCBR 2011. Lecture Notes in Computer Science(), vol 6880. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23291-6_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-23291-6_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23290-9

  • Online ISBN: 978-3-642-23291-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation