Skip to main content

On Classification and Regression

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1532))

Abstract

We address the problem of computing various types of expressive tests for decision tress and regression trees. Using expressive tests is promising, because it may improve the prediction accuracy of trees. The drawback is that computing an optimal test could be costly. We present a unified framework to approach this problem, and we revisit the design of efficient algorithms for computing important special cases. We also prove that it is intractable to compute an optimal conjunction or disjunction

This is a preview of subscription content, log in via an institution.

Buying options

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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. T. Asano, D. Chen, N. Katoh, and T. Tokuyama. Polynomial-time solutions to image segmentations. In Proc. 7th ACM-SIAM Symposium on Discrete Algorithms, pages 104–113, 1996.

    Google Scholar 

  2. L. Breiman, J. H. Friedman, R. A. Olshen, and C. J. Stone. Classification and Regression Trees. Wadsworth, 1984.

    Google Scholar 

  3. T. Fukuda, Y. Morimoto, S. Morishita, and T. Tokuyama. Constructing efficient decision trees by using optimized association rules. In Proceedings of the 22nd VLDB Conference, pages 146–155, Sept. 1996.

    Google Scholar 

  4. T. Fukuda, Y. Morimoto, S. Morishita, and T. Tokuyama. Data mining using twodimensional optimized association rules: Scheme, algorithms, and visualization. In Proceedings of the ACM SIGMOD Conference on Management of Data, pages 13–23, June 1996.

    Google Scholar 

  5. M. R. Garey and D. S. Johnson. Computer and Intractability. A Guide to NP-Completeness. W. H. Freeman, 1979.

    Google Scholar 

  6. N. Katoh. Private communication, Jan. 1997.

    Google Scholar 

  7. C. Lund and M. Yannakakis. On the hardness of approximating minimization problems. J.ACM, 41(5):960–981, 1994.

    Article  MATH  MathSciNet  Google Scholar 

  8. Y. Morimoto, H. Ishii, and S. Morishita. Efficient construction of regression trees with range and region splitting. In Proceedings of the 23rd VLDB Conference, pages 166–175, Aug. 1997.

    Google Scholar 

  9. J. R. Quinlan. Induction of decision trees. Machine Learning, 1:81–106, 1986.

    Google Scholar 

  10. J. R. Quinlan. C4.5: Programs for Machine Learning.Morgan Kaufmann, 1993.

    Google Scholar 

  11. J. R. Quinlan and R. L. Rivest. Inferring decision trees using minimum description length principle. Information and Computation, 80:227–248, 1989.

    Article  MATH  MathSciNet  Google Scholar 

  12. K. Yoda, T. Fukuda, Y. Morimoto, S. Morishita, and T. Tokuyama. Computing optimized rectilinear regions for association rules. In Proceedings of the Third International Conference on Knowledge Discovery and Data Mining, pages 96–103, Aug. 1997.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1998 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Morishita, S. (1998). On Classification and Regression. In: Arikawa, S., Motoda, H. (eds) Discovey Science. DS 1998. Lecture Notes in Computer Science(), vol 1532. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-49292-5_4

Download citation

  • DOI: https://doi.org/10.1007/3-540-49292-5_4

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65390-5

  • Online ISBN: 978-3-540-49292-4

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics