메뉴 건너뛰기




Volumn 103, Issue 1, 1999, Pages 91-105

A fuzzy inductive learning strategy for modular rules

Author keywords

Expert systems; Fuzzy machine learning; Fuzzy sets; Knowledge acquisition; Measure of fuzziness; Membership functions

Indexed keywords


EID: 0003056427     PISSN: 01650114     EISSN: None     Source Type: Journal    
DOI: 10.1016/s0165-0114(97)00181-4     Document Type: Article
Times cited : (47)

References (27)
  • 2
    • 0023325764 scopus 로고
    • Fuzzy learning models in expert systems
    • A.F. Blishun, Fuzzy learning models in expert systems, Fuzzy Sets and Systems 22 (1987) 57-70.
    • (1987) Fuzzy Sets and Systems , vol.22 , pp. 57-70
    • Blishun, A.F.1
  • 5
    • 38248998618 scopus 로고
    • Learning rules for a fuzzy inference model
    • L.M. de Campos, S. Moral, Learning rules for a fuzzy inference model, Fuzzy Sets and Systems 59 (1993) 247-257.
    • (1993) Fuzzy Sets and Systems , vol.59 , pp. 247-257
    • De Campos, L.M.1    Moral, S.2
  • 6
    • 0024103809 scopus 로고
    • PRISM: An algorithm for inducing modular rules
    • J. Cendrowska, PRISM: an algorithm for inducing modular rules, Internat. J. Man-Machine Stud. 27 (1987) 349-370.
    • (1987) Internat. J. Man-Machine Stud. , vol.27 , pp. 349-370
    • Cendrowska, J.1
  • 8
    • 34249966007 scopus 로고
    • The CN2 induction algorithm
    • P. Clark, T. Niblett, The CN2 induction algorithm, Machine Learning 3 (1989) 261-283.
    • (1989) Machine Learning , vol.3 , pp. 261-283
    • Clark, P.1    Niblett, T.2
  • 9
    • 0018923633 scopus 로고
    • Noising around the neighborhood: A new system structure and classification rule for recognition in partially exposed environments
    • B.V. Dasarathy, Noising around the neighborhood: a new system structure and classification rule for recognition in partially exposed environments, IEEE Trans. Pattern Analysis Machine Intelligence 2 (1980) 67-71.
    • (1980) IEEE Trans. Pattern Analysis Machine Intelligence , vol.2 , pp. 67-71
    • Dasarathy, B.V.1
  • 10
    • 0000731222 scopus 로고
    • An inductive learning procedure to identify fuzzy systems
    • M. Delgado, A. Gonzalez, An inductive learning procedure to identify fuzzy systems, Fuzzy Sets and Systems 55 (1993) 121-132.
    • (1993) Fuzzy Sets and Systems , vol.55 , pp. 121-132
    • Delgado, M.1    Gonzalez, A.2
  • 11
    • 0000764772 scopus 로고
    • The use of multiple measurements in taxonomic problems
    • R.A. Fisher, The use of multiple measurements in taxonomic problems, Ann. Eugenics 7 (1936) 179-188.
    • (1936) Ann. Eugenics , vol.7 , pp. 179-188
    • Fisher, R.A.1
  • 12
    • 0029293380 scopus 로고
    • A learning methodology in uncertain and imprecise environments
    • A. Gonzalez, A learning methodology in uncertain and imprecise environments, Internat. J. Intelligent Systems 10 (1995) 357-371.
    • (1995) Internat. J. Intelligent Systems , vol.10 , pp. 357-371
    • Gonzalez, A.1
  • 13
    • 0028530086 scopus 로고
    • Generalizing version spaces
    • H. Hirsh, Generalizing version spaces, Machine Learning 17 (1994) 5-46.
    • (1994) Machine Learning , vol.17 , pp. 5-46
    • Hirsh, H.1
  • 14
    • 0031094448 scopus 로고    scopus 로고
    • A generalized version space learning algorithm for noisy and uncertain data
    • T.P. Hong, S.S. Tseng, A generalized version space learning algorithm for noisy and uncertain data, IEEE Trans. Knowledge Data Eng. 9 (1997) 336-340.
    • (1997) IEEE Trans. Knowledge Data Eng. , vol.9 , pp. 336-340
    • Hong, T.P.1    Tseng, S.S.2
  • 15
    • 0039840920 scopus 로고
    • Neuro-fuzzy ID3 - A method of inducing decision trees with linear programming for maximizing entropy and an algebraic method for incremental learning
    • Nagoya, Japan
    • H. Ichihashi, T. Shirai, K. Nagasaka, T. Miyoshi, Neuro-fuzzy ID3 - a method of inducing decision trees with linear programming for maximizing entropy and an algebraic method for incremental learning, Proc. IEEE WWW on Fuzzy Logic and Neural Networks/Genetic Algorithms, Nagoya, Japan, 1994, pp. 23-33.
    • (1994) Proc. IEEE WWW on Fuzzy Logic and Neural Networks/Genetic Algorithms , pp. 23-33
    • Ichihashi, H.1    Shirai, T.2    Nagasaka, K.3    Miyoshi, T.4
  • 16
    • 0003069184 scopus 로고
    • Fuzzy logic with linguistic quantifiers in inductive learning
    • L.A. Zadeh, J. Kacprzyk (Eds.), Wiley, New York
    • J. Kacprzyk, C. Iwanski, Fuzzy logic with linguistic quantifiers in inductive learning, in: L.A. Zadeh, J. Kacprzyk (Eds.), Fuzzy Logic for the Management of Uncertainty, Wiley, New York, 1992, pp. 465-478.
    • (1992) Fuzzy Logic for the Management of Uncertainty , pp. 465-478
    • Kacprzyk, J.1    Iwanski, C.2
  • 20
    • 0002889808 scopus 로고
    • Decision tree as probabilistic classifier
    • Morgan Kaufmann, San Mateo, CA
    • J.R. Quinlan, Decision tree as probabilistic classifier, Proc. 4th Internat. Machine Learning Workshop, Morgan Kaufmann, San Mateo, CA, 1987, pp. 31-37.
    • (1987) Proc. 4th Internat. Machine Learning Workshop , pp. 31-37
    • Quinlan, J.R.1
  • 25
    • 0002079564 scopus 로고
    • Fuzzy-ID3: A class of methods for automatic knowledge acquisition
    • Iizuka, Japan
    • R. Weber, Fuzzy-ID3: a class of methods for automatic knowledge acquisition, Proc. 2nd Internat. Conf. on Fuzzy Logic and Neural Networks, Iizuka, Japan, 1992, pp. 265-268.
    • (1992) Proc. 2nd Internat. Conf. on Fuzzy Logic and Neural Networks , pp. 265-268
    • Weber, R.1
  • 26
    • 0020831194 scopus 로고
    • A general concept of fuzzy connectives, negations and implications based on t-norms and t-conorms
    • S. Weber, A general concept of fuzzy connectives, negations and implications based on t-norms and t-conorms, Fuzzy Sets and Systems 11 (1983) 115-134.
    • (1983) Fuzzy Sets and Systems , vol.11 , pp. 115-134
    • Weber, S.1
  • 27
    • 0000868331 scopus 로고
    • Induction of fuzzy decision trees
    • Y. Yuan, M.J. Shaw, Induction of fuzzy decision trees, Fuzzy Sets and Systems 69 (1995) 125-139.
    • (1995) Fuzzy Sets and Systems , vol.69 , pp. 125-139
    • Yuan, Y.1    Shaw, M.J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.