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Relationships between Depth and Number of Misclassifications for Decision Trees

  • Igor Chikalov
  • Shahid Hussain
  • Mikhail Moshkov
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6743)

Abstract

This paper describes a new tool for the study of relationships between depth and number of misclassifications for decision trees. In addition to the algorithm the paper also presents the results of experiments with three datasets from UCI Machine Learning Repository [3].

Keywords

decision trees depth number of misclassifications 

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References

  1. 1.
    Alkhalid, A., Chikalov, I., Moshkov, M.: On algorithm for building of optimal α-decision trees. In: Szczuka, M., Kryszkiewicz, M., Ramanna, S., Jensen, R., Hu, Q. (eds.) RSCTC 2010. LNCS(LNAI), vol. 6086, pp. 438–445. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  2. 2.
    Chikalov, I., Moshkov, M., Zelentsova, M.: On optimization of decision trees. In: Peters, J.F., Skowron, A. (eds.) Transactions on Rough Sets IV. LNCS, vol. 3700, pp. 18–36. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  3. 3.
    Frank, A., Asuncion, A.: UCI Machine Learning Repository. University of California, School of Information and Computer Science, Irvine, CA (2010), http://archive.ics.uci.edu/ml Google Scholar
  4. 4.
    Pawlak, Z.: Rough sets – Theoretical Aspects of Reasoning About Data. Kluwer Academic Publishers, Dordrecht (1991)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Igor Chikalov
    • 1
  • Shahid Hussain
    • 1
  • Mikhail Moshkov
    • 1
  1. 1.Mathematical and Computer Sciences & Engineering DivisionKing Abdullah University of Science and TechnologyThuwalSaudi Arabia

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