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Volumn 6, Issue 2, 1998, Pages 171-178

Missing values and learning of fuzzy rules

Author keywords

Classification; Fuzzy Rules; Learning; Missing Values

Indexed keywords


EID: 0003001242     PISSN: 02184885     EISSN: None     Source Type: Journal    
DOI: 10.1142/S021848859800015X     Document Type: Article
Times cited : (19)

References (11)
  • 1
    • 0000652102 scopus 로고
    • Some Solutions to the Missing Feature Problem in Vision
    • S. J. Hanson, J. D. Cowan, and C. L. Giles, editors, California, Morgan Kaufmann
    • S. Ahmad and V. Tresp. Some Solutions to the Missing Feature Problem in Vision. In S. J. Hanson, J. D. Cowan, and C. L. Giles, editors, Advances in Neural Information Processing Systems, 5, pages 393-400, California, 1993. Morgan Kaufmann.
    • (1993) Advances in Neural Information Processing Systems , vol.5 , pp. 393-400
    • Ahmad, S.1    Tresp, V.2
  • 3
    • 0001126591 scopus 로고
    • Learning Fuzzy rule-based Neural Networks for Control
    • California, Morgan Kaufmann
    • C. M. Higgins and R. M. Goodman. Learning Fuzzy rule-based Neural Networks for Control. In Advances in Neural Information Processing Systems, 5, pages 350-357, California, 1993. Morgan Kaufmann.
    • (1993) Advances in Neural Information Processing Systems , vol.5 , pp. 350-357
    • Higgins, C.M.1    Goodman, R.M.2
  • 4
    • 84949788351 scopus 로고    scopus 로고
    • Techniques for Dealing with Missing Values in Classification
    • X. Liu, P. Cohen, and M. R. Berthold, editors, Lecture Notes in Computer Science, LNCS1280, Springer Verlag
    • W. Z. Liu, A. P., White, S. G. Thompson, and M. A. Bramer. Techniques for Dealing with Missing Values in Classification. In X. Liu, P. Cohen, and M. R. Berthold, editors, Advances in Intelligent Data Analysis, Lecture Notes in Computer Science, LNCS1280, pages 527-536, Springer Verlag, 1997.
    • (1997) Advances in Intelligent Data Analysis , pp. 527-536
    • Liu, W.Z.1    White, A.P.2    Thompson, S.G.3    Bramer, M.A.4
  • 6
    • 0026927202 scopus 로고
    • Fuzzy min-max Neural Networks - Part 1: Classification
    • September
    • Patrick K. Simpson. Fuzzy min-max Neural Networks - Part 1: Classification. IEEE Transactions on Neural Networks, 3(5):776-786, September 1992.
    • (1992) IEEE Transactions on Neural Networks , vol.3 , Issue.5 , pp. 776-786
    • Simpson, P.K.1
  • 7
    • 0027542561 scopus 로고
    • Fuzzy min-max Neural Networks - Part 2: Clustering
    • January
    • Patrick K. Simpson. Fuzzy min-max Neural Networks - Part 2: Clustering. IEEE Transactions on Fuzzy Systems, 1(1):32-45, January 1993.
    • (1993) IEEE Transactions on Fuzzy Systems , vol.1 , Issue.1 , pp. 32-45
    • Simpson, P.K.1
  • 8
    • 0000684508 scopus 로고
    • Training Neural Networks with Deficient Data
    • J. D. Cowan, G. Tesauro, and J. Alspector, editors, California, Morgan Kaufmann
    • V. Tresp, S. Ahmad, and R. Neuneier. Training Neural Networks with Deficient Data. In J. D. Cowan, G. Tesauro, and J. Alspector, editors, Advances in Neural Information Processing Systems, 6, pages 128-135, California, 1994. Morgan Kaufmann.
    • (1994) Advances in Neural Information Processing Systems , vol.6 , pp. 128-135
    • Tresp, V.1    Ahmad, S.2    Neuneier, R.3
  • 10
    • 0028534525 scopus 로고
    • Soft computing and Fuzzy Logic
    • November
    • Lotfi A. Zadeh. Soft computing and Fuzzy Logic. IEEE Software, pages 48-56, November 1994.
    • (1994) IEEE Software , pp. 48-56
    • Zadeh, L.A.1
  • 11
    • 0002465901 scopus 로고    scopus 로고
    • Fuzzy Logic and the Calculi of Fuzzy Rules and Fuzzy Graphs: A Precis
    • Lotfi A. Zadeh. Fuzzy Logic and the Calculi of Fuzzy Rules and Fuzzy Graphs: A Precis. Multi. Val. Logic, 1, pages 1-38, 1996.
    • (1996) Multi. Val. Logic , vol.1 , pp. 1-38
    • Zadeh, L.A.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.