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Volumn 1, Issue , 2004, Pages 73-77

Getting adaptability or expressivity in inductive logic programming by using fuzzy predicates

Author keywords

[No Author keywords available]

Indexed keywords

CARDINALITY; FUZZY PREDICATES; INDUCTIVE LOGIC PROGRAMMING (ILP); LEARNING FUZZY RULES;

EID: 11144313109     PISSN: 10987584     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/FUZZY.2004.1375691     Document Type: Conference Paper
Times cited : (2)

References (18)
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    • Fayyad, U.M.1    Irani, K.B.2
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    • R. Bajcsy, editor, Morgan Kaufmann
    • U.M. Fayyad and K.B. Irani. Multi-interval discretization of continuous-valued attributes for classification learning. In R. Bajcsy, editor, Proceedings of the 13th International Joint Conference on Artificial Intelligence, pages 1022-1027. Morgan Kaufmann, 1993.
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    • J.C. Bezdek, D. Dubois, H. Prade, eds., The Handbooks of Fuzzy Sets Series, Kluwer Academic Publishers
    • D. Nauck and R. Kruse. Neuro-tuzzy methods in fuzzy rule generation. In Fuzzy Sets in Approximate Reasoning and Information Systems, (J.C. Bezdek, D. Dubois, H. Prade, eds., The Handbooks of Fuzzy Sets Series, pages 305-334. Kluwer Academic Publishers, 1999.
    • (1999) Fuzzy Sets in Approximate Reasoning and Information Systems , pp. 305-334
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    • The benefits of using fuzzy discretisation for the induction of logic rules
    • In submission
    • M. Serrurier and H. Prade. The benefits of using fuzzy discretisation for the induction of logic rules. IRIT Tech. Rep., 2004. In submission.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.