A hybrid decision tree model based on credibility theory

Advances in Soft Computing

Volumn 40, Issue , 2007, Pages 930-939

  Qi, Chengming ^a  

^a BEIJING UNION UNIVERSITY   (China)

Author keywords

Classification; Credibility theory; Fuzzy decision tree; Fuzzy entropy

Indexed keywords

EID: 58149240901     PISSN: 16153871     EISSN: 18600794     Source Type: Book Series    
DOI: 10.1007/978-3-540-71441-5_101     Document Type: Conference Paper

References (28)

1. Quinlan (1986) Induction on decision trees. Machine Learning,1(1):81-106
2. B. Bouchon-Meunier, C. Marsala, and M. Ramdani(1997) Learning from imperfect data. In D. Dubois, H. Prade, and R. R. Yager editors, Fuzzy Information Engineering: A Guided Tour of Applications, pages 139-148. John Wileys and Sons
3. B. Bouchon-Meunicr and C. Marsala(1999) Learning fuzzy decision rules. In D. Dubois J. Bczdek and H. Prade, editors, Fuzzy Sets in Approximate Reasoning and Information Systems, volume 3 of Handbook of Fuzzy Sets, chapter 4. Kluwer Academic Publisher
4. B. Lent, 11. Swami, and J. Widom (1997) Clustering association rule. In Proceedings of the 13th International Conference on Data Engineering, pages 220-231, Birmingham, UK. IEEE Computer Society Press
5. Liu B(2004) Uncertainty Theory: An Introduction to its Axiomatic Foundations, Springer-Verlag, Berlin
6. Zadeh LA(1965) Fuzzy sets, Information and Control, Vol.8, 338-353
7. Zadeh LA(1978) Fuzzy sets as a basis for a theory of possibility, Fuzzy Sets and Systems, Vol.1, 3-28
8. Liu B, and Liu YK(2002) Expected value of fuzzy variable and fuzzy expected value models, IEEE Transactions on Fuzzy Systems, Vol.10, No.4,445-450
9. Li X, and Liu B(2006) New independence definition of fuzzy random variable and random fuzzy variable, World Journal of Modelling and Simulation
10. Loo SG(1977) Measures of fuzziness, Cybernetica,Vol.20, 201-210
11. Yager RR(1979) On measures of fuzziness and negation, Part I: Membership in the unit interval, International Journal of General Systems, Vol.5, 221-229
12. Yager RR(1980) On measures of fuzziness and negation, Part II: Lattices, Information and Control, Vol.44, 236-260
13. Yager RR(1983) Entropy and specificity in a mathematical theory of evidence, International Journal of General Systems,Vol.9, 249-260
14. Yager RR (1995) Measures of entropy and fuzziness related to aggregation operators, Information Sciences,Vol.82, 147-166
15. Liu XC (1992) Entropy, distance measure and similarity measure of fuzzy sets and their relations, Fuzzy Sets and Systems,Vol.52, 305-318
16. Pal NR(1992) and Pal SK, Higher order fuzzy entropy and hybrid entropy of a set, Information Sciences, Vol.61, 211-231
17. Pal NR(1994) and Bezdek JC, Measuring fuzzy uncertainty, IEEE Transactions on Fuzzy Systems,Vol.2, 107-118
18. De Luca A, and Termini S(1972) A definition of nonprobabilistic entropy in the setting of fuzzy sets theory, Information and Control,Vol.20, 301-312
19. Li P, and Liu B(2005) Entropy of credibility distributions for fuzzy variables, Technical Report
20. M. Umano, H. Okamoto, I. Hatono, H. Tamura, F. Kawachi, S. Umedzu, and J. Kinoshita (1994) Fuzzy decision trees by fuzzy ID3 algorithm and its application to diagnosis systems. In Proceedings of the 3rd IEEE Conference on Fuzzy Systems, volume 3, pages 2113-2118, Orlando
21. M. R. Civanlar and H. J. Trussell(1986) "Constructing membership functions using statistical data," Fuzzy Sets and Systems,vol. 18, pp. 1-14
22. T. Kohonen(1988) "Self-Organization and Association Memory" Springer, Berlin
23. Y. Yuan and M. J. Shaw(1995) "Induction of fuzzy decision trees," Fuzzy Sets and Systems, vol. 69, pp. 125-139
24. K. J. Cios and L. M. Sztandera (1992) "Continuous ID3 algorithm with fuzzy entropy measures," Proc. IEEE Int. Conf. Fuzzy Syst,pp. 469-476
25. L. Breiman, J. H. Friedman, J. A. Olshen, and C. J. Stone (1984) Classification and Regression Frees, Wadsworth International Group, Belmont, CA
26. J. Mingers(1989) "An empirical comparison of pruning methods for decision-tree induction," Machine Learning, vol. 4, pp. 227-243
27. J. Frnkranz(1997) "Pruning algorithms for rule learning," Machine Learning,vol. 27, pp. 139-172
28. J. Catlett(1991) On changing continuous attributes into ordered discrete attributes. In Y. Kodratoff, editor proc. of 5th European Working Sessions on Learning, pages 164-178. Springer, Berlin, Heidelherg, Porto, Portugal