Skip to main content
SpringerLink
Log in

An Evolutionary Algorithm for Oblique Decision Tree Induction

  • Conference paper
Artificial Intelligence and Soft Computing - ICAISC 2004 (ICAISC 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3070))

Included in the following conference series:

Abstract

In the paper, a new evolutionary approach to induction of oblique decision trees is described. In each non-terminal node, the specialized evolutionary algorithm is applied to search for a splitting hyper-plane. The feature selection is embedded into the algorithm, which allows to eliminate redundant and noisy features at each node. The experimental evaluation of the proposed approach is presented on both synthetic and real datasets.

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. Blake, C., Keogh, E., Merz, C.: UCI repository of machine learning databases, University of California, Dept. of Computer Science, Irvine, CA (1998), http://www.ics.uci.edu/~mlearn/MLRepository.html

  2. Bobrowski, L., Krȩtowski, M.: Induction of multivariate decision trees by using dipolar criteria. In: Zighed, D.A., Komorowski, J., Żytkow, J.M. (eds.) PKDD 2000. LNCS (LNAI), vol. 1910, pp. 331–336. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  3. Bobrowski, L.: Piecewise-linear classifiers, formal neurons and separability of the learning sets. In: Proc. of 13th Int. Conf. on Pattern Recognition, pp. 224–228 (1996)

    Google Scholar 

  4. Breiman, L., Friedman, J., Olshen, R., Stone, C.: Classification and Regression Trees. Wadsworth Int. Group (1984)

    Google Scholar 

  5. Cantu-Paz, E., Kamath, C.: Inducing oblique decision trees with evolutionary algorithms. IEEE Transcations on Evolutionary Computation 7(1), 54–68 (2003)

    Article  Google Scholar 

  6. Chai, B., Huang, T., Zhuang, X., Zhao, Y., Sklansky, J.: Piecewise-linear classifiers using binary tree structure and genetic algorithm. Pattern Recognition 29(11), 1905–1917 (1996)

    Article  Google Scholar 

  7. Duda, O., Heart, P., Stork, D.: Pattern Classification, 2nd edn. J. Wiley, Chichester (2001)

    MATH  Google Scholar 

  8. Gama, J., Brazdil, P.: Linear tree. Inteligent Data Analysis 3(1), 1–22 (1999)

    Article  MATH  Google Scholar 

  9. Michalewicz, Z.: Genetic Algorithms + Data Structures = Evolution Programs, 3rd edn. Springer, Heidelberg (1996)

    MATH  Google Scholar 

  10. Murthy, S., Kasif, S., Salzberg, S.: A system for induction of oblique decision trees. Journal of Artificial Intelligence Research 2, 1–33 (1994)

    MATH  Google Scholar 

  11. Murthy, S.: Automatic construction of decision trees from data: A multidisciplinary survey. Data Mining and Knowledge Discovery 2, 345–389 (1998)

    Article  MathSciNet  Google Scholar 

  12. Quinlan, J.: C4.5: Programs for Machine Learning. Morgan Kaufmann, San Francisco (1993)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Computer Science, Białystok Technical University, Wiejska 45a, 15-351, Białystok, Poland

    Marek Krȩtowski

Authors
  1. Marek Krȩtowski
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Artificial Intelligence, Academy of Humanities and Economics, Poland

    Leszek Rutkowski

  2. German Research Center of Artificial Intelligence (DFKI), Germany

    Jörg H. Siekmann

  3. Institute of Automatics, AGH University of Science and Technology, Al. Mickiewicza 30, PL-30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  4. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Initiative in Soft Computing (BISC), 94720-1776, Berkeley, CA

    Lotfi A. Zadeh

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Krȩtowski, M. (2004). An Evolutionary Algorithm for Oblique Decision Tree Induction. In: Rutkowski, L., Siekmann, J.H., Tadeusiewicz, R., Zadeh, L.A. (eds) Artificial Intelligence and Soft Computing - ICAISC 2004. ICAISC 2004. Lecture Notes in Computer Science(), vol 3070. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24844-6_63

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-24844-6_63

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22123-4

  • Online ISBN: 978-3-540-24844-6

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation