Why fuzzy decision trees are dood rankers

IEEE Transactions on Fuzzy Systems

Volumn 17, Issue 6, 2009, Pages 1233-1244

  Hüllermeier, Eyke ^a   Vanderlooy, Stijn ^b  

^a PHILIPPS UNIVERSITY MARBURG   (Germany)

^b MAASTRICHT UNIVERSITY   (Netherlands)

Author keywords

Area under the receiver operating characteristic (ROC) curve; Bipartite ranking; Decision trees; Fine granular membership degrees; Fuzzy inference; Laplace correction; Soft feature splits

Indexed keywords

AREA UNDER THE RECEIVER OPERATING CHARACTERISTIC (ROC) CURVE; DECISION TREE INDUCTION; FUZZY DECISION TREES; FUZZY EXTENSION; KEY PROBLEMS; MACHINE-LEARNING; MEMBERSHIP DEGREES; PERFORMANCE TASKS; RANKING CRITERION; RANKING PERFORMANCE; RECEIVER OPERATING CHARACTERISTIC CURVES;

FUZZY CONTROL; FUZZY INFERENCE; LAPLACE TRANSFORMS;

DECISION TREES;

EID: 71049130644     PISSN: 10636706     EISSN: None     Source Type: Journal    
DOI: 10.1109/TFUZZ.2009.2026640     Document Type: Article

References (32)

1. F. Provost and V. Kolluri, "A survey of methods for scaling up inductive algorithms," Data Mining Knowl. Discovery, vol.3, no.2, pp. 131-169, 1999.
2. P. Geurts, D. Ernst, and L. Wehenkel, "Extremely randomized trees," Mach. Learn., vol.36, no.1, pp. 3-42, 2006.
3. L. Breiman, J. Friedman, C. Stone, and R. Olshen, Classification and Regression Trees. Boca Raton, FL: Chapman & Hall/CRC, 1984.
4. R. Quinlan, C4.5: Programs for Machine Learning. San Francisco, CA: Morgan Kaufmann, 1993.
5. W. Cohen, R. Shapire, and Y. Singer, "Learning to order things," in Advances in Neural Information Processing Systems (NIPS), M. Jordan, M. Kearns, and S. Solla, Eds. Denver, CO: MIT Press, Dec. 2-4, 1997, pp. 451-457.
6. P. Flach and E. Matsubara, "A simple lexicographic ranker and probability estimator," in Proc. 18th Eur. Conf. Mach. Learn., J. Kok, R. L. de Ḿantaras, S. Matwin, D. Mladenic, and A. Skowron, Eds. Warsaw, Poland: Springer-Verlag, Sep. 17-21, 2007, pp. 575-582.
7. A. Bradley, "The use of the area under the ROC curve in the evaluation of machine learning algorithms," Pattern Recognit., vol.30, no.7, pp. 1145-1159, 1997.
8. F. Provost and P. Domingos, "Tree induction for probability-based ranking," Mach. Learn., vol.52, no.3, pp. 199-215, 2003.
9. C. Ferri, P. Flach, and J. Hernández-Orallo, "Improving the AUC of probabilistic estimation trees," in Proc. 14th Eur. Conf. Mach. Learn., N. Lavrac, D. Gamberger, L. Todorovski, and H. Blockeel, Eds. Cavtat-Dubrovnik, Croatia: Springer-Verlag, Sep. 22-26, 2003, pp. 121-132.
10. C. Olaru and L. Wehenkel, "A complete fuzzy decision tree technique," Fuzzy Sets Syst., vol.138, no.2, pp. 221-254, 2003.
11. T. Fawcett, "An introduction to ROC analysis," Pattern Recognit. Lett., vol.27, no.8, pp. 861-874, 2006.
12. C. Ferri, P. Flach, and J. Hernández-Orallo, "Learning decision trees using the area under the ROC curve," in Proc. 19th Int. Conf. Mach. Learn., C. Sammut and A. Hoffmann, Eds. Sydney, N.S.W., Australia: Morgan Kaufmann, Jul. 8-12, 2002, pp. 139-146.
13. C. Bishop, Pattern Recognition and Machine Learning. NewYork: Springer-Verlag, 2007.
14. P. Smyth, A. Gray, and U. Fayyad, "Retrofitting decision tree classifiers using kernel density estimation," in Proc. 12th Int. Conf. Mach. Learn., A. Prieditis and S. Russell, Eds. Tahoe City, CA: Morgan Kaufmann, Jul. 9-12, 1995, pp. 506-514.
15. R. Kohavi, "Scaling up the accuracy of naive-Bayes classifiers: A decision-tree hybrid," in Proc. 2nd Int. Conf. Knowl. Discovery Data Mining, E. Simoudis, J. Han, and U. Fayyad, Eds. Portland, OR: AAAI, Aug. 2-4, 1996, pp. 202-207.
16. B. Zadrozny and C. Elkan, "Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers," in Proc. 18th Int. Conf. Mach. Learn., C. Brodley and A. P. Danyluk, Eds. San Francisco, CA: Morgan Kaufmann, Jun. 28-Jul. 1, 2001, pp. 609-616.
17. B. Wang and H. Zhang, "Improving the ranking performance of decision trees," in Proc. 17th Eur. Conf. Mach. Learn., J. Furnkranz, T. Scheffer, and M. Spiliopoulou, Eds. Berlin, Germany: Springer-Verlag, Sep. 18-22, 2006, pp. 461-472.
18. H. Zhang and J. Su, "Learning probabilistic decision trees for AUC," Pattern Recognit. Lett., vol.27, no.8, pp. 892-899, 2006.
19. S. Clémençon and N. Vayatis, "Approximation of the optimal ROC curve and a tree-based ranking algorithm," in Proc. 19th Int. Conf. Algorithmic Learn. Theory, Y. Freund, L. Györfi, G. Tuŕan, and T. Zeugmann, Eds. Budapest, Hungary: Springer-Verlag, Oct. 13-16, 2008, pp. 22-37.
20. C. Ling and R. Yan, "Decision tree with better ranking," in Proc. 20th Int. Conf. Mach. Learn., T. Fawcett and N. Mishra, Eds. Washington, DC: AAAI, Aug. 21-24, 2003, pp. 480-487.
21. A. Asuncion and D. Newman. (2007). UCI machine learning repository [Online]. Available: http://www.ics.uci.edu/?mlearn/{MLR}epository.html
22. I. Witten and E. Frank, Data Mining: Practical Machine Learning Tools and Techniques, 2nd ed. San Francisco, CA: Morgan Kaufmann, 2005.
23. J. Demsar, "Statistical comparisons of classifiers over multiple data sets," J. Mach. Learn. Res., vol.7, pp. 1-30, 2006. (Pubitemid 43022939)
24. E. Hüllermeier and S. Vanderlooy, "An empirical and formal analysis of decision trees for ranking," Philipps Universität Marburg, Marburg, Germany, Tech. Rep. Comput. Sci. Series 56, 2008.
25. R. Weber, "Fuzzy ID3: A class of methods for automatic knowledge acquisition," in Proc. 2nd Int. Conf. Fuzzy Logic Neural Netw., Iizuka, Japan, Jul. 17-22, 1992, pp. 265-268.
26. C. Janikow, "Fuzzy decision trees: Issues and methods," IEEE Trans. Syst., Man, Cybern., vol.28, no.1, pp. 1-14, Feb. 1998.
27. C. Marsala and B. Bouchon-Meunier, "Fuzzy partitioning using mathematical morphology in a learning scheme," in Proc. 5th IEEE Int. Conf. Fuzzy Syst., New Orleans, LA, Sep. 8-11, 1996, pp. 1512-1517.
28. C. Marsala and B. Bouchon-Meunier, "An adaptable system to construct fuzzy decision trees," in Proc. 18th North Amer. Fuzzy Inf. Process. Soc. Conf., New York, Jun. 10-12, 1999, pp. 223-297.
29. W. Pedrycz and Z. Sosnowski, "Designing decision trees with the use of fuzzy granulation," IEEE Trans. Syst., Man, Cybern. A, Syst., Humans, vol.30, no.2, pp. 151-159, Mar. 2000.
30. W. Pedrycz and Z. Sosnowski, "The design of decision trees in the framework of granular data and their application to software quality models," Fuzzy Sets Syst., vol.123, no.3, pp. 271-290, 2001.
31. W. Pedrycz and Z. Sosnowski, "C-Fuzzy decision trees," IEEE Trans. Syst., Man, Cybern. C, Appl. Rev., vol.35, no.4, pp. 498-511, Nov. 2005.
32. X. Wang, B. Chen, G. Qian, and F. Ye, "On the optimization of fuzzy decision trees," Fuzzy Sets Syst., vol.112, no.1, pp. 117-125, 2000.