Predicting Nearly As Well As the Best Pruning of a Decision Tree

Machine Learning

Volumn 27, Issue 1, 1997, Pages 51-68

  Helmbold, David P ^a   Schapire, Robert E ^b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b AT AND T LABS RESEARCH   (United States)

Author keywords

Decision trees; On line learning; Prediction; Pruning

Indexed keywords

COMPUTATIONAL COMPLEXITY; DECISION THEORY; LEARNING SYSTEMS; ONLINE SYSTEMS; THEOREM PROVING; TREES (MATHEMATICS);

DECISION TREE; PRUNING ALGORITHMS;

LEARNING ALGORITHMS;

EID: 0031122905     PISSN: 08856125     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1007396710653     Document Type: Article

References (23)

1. Breiman, Leo, Friedman, Jerome H., Olshen, Richard A. & Stone, Charles J. 1984 Classification and Regression Trees. Wadsworth International Group.
2. Buntine, Wray. 1992. Learning classification trees. Statistics and Computing, 2:63-73.
3. Buntine, Wray Lindsay. 1990. A Theory of Learning Classification Rules. PhD thesis, University of Technology, Sydney, 1990.
4. Cesa-Bianchi, Nicolò , Freund, Yoav, Helmbold, David P., Haussler, David, Schapire, Robert E., & Warmuth, Manfred K. 1993. How to use expert advice. In Proceedings of the Twenty-Fifth Annual ACM Symposium on the Theory of Computing, pages 382-391, 1993. To appear, Journal of the Association for Computing Machinery.
5. Cesa-Bianchi, Nicolò , Freund, Yoav, Helmbold, David P., Haussler, David, Schapire, Robert E., & Warmuth, Manfred K. 1993. How to use expert advice. In Proceedings of the Twenty-Fifth Annual ACM Symposium on the Theory of Computing, pages 382-391, 1993. To appear, Journal of the Association for Computing Machinery.
6. Freund, Yoav & Schapire, Robert E. 1995. A decision-theoretic generalization of on-line learning and an application to boosting. In Computational Learning Theory: Second European Conference, EuroCOLT '95, pages 23-37. Springer-Verlag. To appear, Journal of Computer and System Sciences.
7. Freund, Yoav & Schapire, Robert E. 1995. A decision-theoretic generalization of on-line learning and an application to boosting. In Computational Learning Theory: Second European Conference, EuroCOLT '95, pages 23-37. Springer-Verlag. To appear, Journal of Computer and System Sciences.
8. Hastie, Trevor & Pregibon, Daryl. 1990. Shrinking trees. Technical report, AT&T Bell Laboratories.
9. Kivinen, Jyrki & Warmuth, Manfred K. Using experts for predicting continuous outcomes. In Computational Learning Theory: EuroCOLT '93, pages 109-120. Springer-Verlag.
10. Kwok, Suk Wah & Carter, Chris. 1990. Multiple decision trees. In Ross D. Shachter, Tod S. Levitt, Laveen N. Kanal, and John F. Lemmer, editors, Uncertainty in Artificial Intelligence 4, pages 327-335. North-Holland.
11. Littlestone, Nick. 1988. Learning when irrelevant attributes abound: A new linear-threshold algorithm. Machine Learning, 2:285-318.
12. Littlestone, Nick & Warmuth, Manfred K. 1994. The weighted majority algorithm. Information and Computation, 108:212-261.
13. Oliver, Jonathan J. & Hand, David. 1994. Averaging over decision stumps. In Machine Learning: ECML-94, pages 231-241. Springer-Verlag.
14. Oliver, Jonathan J. & Hand David J. 1995. On pruning and averaging decision trees. In Proceedings of the Twelfth International Conference on Machine Learning, pages 430-437.
15. Quinlan, J. Ross. 1993. C4.5: Programs for Machine Learning. Morgan Kaufmann.
16. Rissanen, Jorma. 1983. A universal data compression system. IEEE Transactions on Information Theory, IT-29(5):656-664.
17. Ron, Dana, Singer, Yoram & Tishby, Naftali. 1994. Learning probabilistic automata with variable memory length. In Proceedings of the Seventh Annual ACM Conference on Computational Learning Theory, pages 35-46.
18. Vovk, Volodimir G. 1990. Aggregating strategies. In Proceedings of the Third Annual Workshop on Computational Learning Theory, pages 371-383.
19. Weinberger, Marcelo J., Lempel, Abraham & Ziv, Jacob. 1992. A sequential algorithm for the universal coding of finite-memory sources. IEEE Transactions on Information Theory, 38(3): 1002-1014.
20. Weinberger, Marcelo J., Merhav, Neri & Feder, Meir. 1994. Optimal sequential probability assignment for individual sequences. IEEE Transactions on Information Theory, 40(2):384-396.
21. Weinberger, Marcelo J., Rissanen, Jorma J. & Feder, Meir. 1995. A universal finite memory source. IEEE Transactions on Information Theory, 41(3):643-652.
22. Willems, Frans M. J., Shtarkov, Yuri M. & Tjalkens, Tjalling J. 1993. Context tree weighting: a sequential universal source coding procedure for FSMX sources. In Proceedings 1993 IEEE International Symposium on Information Theory, page 59.
23. Willems, Frans M. J., Shtarkov, Yuri M. & Tjalkens, Tjalling J. 1995. The context tree weighting method: basic properties. IEEE Transactions on Information Theory, 41 (3):653-664.