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Volumn 1321, Issue , 1997, Pages 24-35

Handling continuous data in top-down induction of first-order rules

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; HEURISTIC ALGORITHMS; LEARNING SYSTEMS;

EID: 84961306865     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-63576-9_93     Document Type: Conference Paper
Times cited : (7)

References (31)
  • 1
    • 85009499689 scopus 로고
    • Constructive learning with continuous-valued attributes
    • B. Bouchon, L. Saitta, and R.R. Yager (Eds.), LNCS 313, Berlin: Springer-Verlag
    • F. Bergadano, and R. Bisio. Constructive learning with continuous-valued attributes. In B. Bouchon, L. Saitta, and R.R. Yager (Eds.), Uncertainty and Intelligent Systems., LNCS 313, Berlin: Springer-Verlag, pp. 54-162,1988.
    • (1988) Uncertainty and Intelligent Systems , pp. 54-162
    • Bergadano, F.1    Bisio, R.2
  • 2
    • 0342684934 scopus 로고
    • Learning quantitative features in a symbolic environment
    • Z.W. Ras and M. Zemankova (Eds.), LNAIS42, Berlin: Springer-Verlag
    • M. Botta, and A.Giordana. Learning quantitative features in a symbolic environment In Z.W. Ras and M. Zemankova (Eds.), Methodologies for Intelligent Systems, LNAIS42, Berlin: Springer-Verlag, pp. 296-305,1991.
    • (1991) Methodologies for Intelligent Systems , pp. 296-305
    • Botta, M.1    Giordana, A.2
  • 3
    • 0024084964 scopus 로고
    • Generalized subsumption ami its application to induction and redundancy
    • W. Buntine. Generalized subsumption ami its application to induction and redundancy. Artificial Intelligence, vol. 36, no. 2, pp. 375-399,1988.
    • (1988) Artificial Intelligence , vol.36 , Issue.2 , pp. 375-399
    • Buntine, W.1
  • 4
    • 0023294265 scopus 로고
    • Generating and generalizing models of visual objects
    • J.H. Connell and M. Brady. Generating and generalizing models of visual objects. Artificial Intelligence, vol. 31, no. 2, pp. 159-183,1987.
    • (1987) Artificial Intelligence , vol.31 , Issue.2 , pp. 159-183
    • Connell, J.H.1    Brady, M.2
  • 6
    • 84948981620 scopus 로고
    • Handling real numbers in ILP: A step towards better behavioural clones (Extended abstract)
    • N. Lavrac and S. Wrobel (Eds.), LNAI 912, Berlin: Springer
    • S. Dzeroski, L. Todorovski, and T. Urbancic. Handling real numbers in ILP: A step towards better behavioural clones (Extended abstract). In N. Lavrac and S. Wrobel (Eds.), Machine Learning. ECML95, LNAI 912, Berlin: Springer, pp. 283-286,1995.
    • (1995) Machine Learning. ECML95 , pp. 283-286
    • Dzeroski, S.1    Todorovski, L.2    Urbancic, T.3
  • 7
    • 0343119200 scopus 로고    scopus 로고
    • Applications of inductive logic programming
    • L. De Raedt (Ed.), Amsterdam: IOS Press
    • S. Dzeroski, and I. Bratko. Applications of inductive logic programming. In L. De Raedt (Ed.), Advances in Inductive Logic Programming, Amsterdam: IOS Press, pp. 65-81,1996.
    • (1996) Advances in Inductive Logic Programming , pp. 65-81
    • Dzeroski, S.1    Bratko, I.2
  • 8
    • 0343555117 scopus 로고
    • Incorporating statistical techniques into empirical symbolic learning systems
    • D.J. Hand (Ed.), London: Chapman & Hall
    • F. Esposito, D. Malerba, and G. Semeraro. Incorporating statistical techniques into empirical symbolic learning systems. In D.J. Hand (Ed.), Artificial Intelligence Frontiers in Statistics, London: Chapman & Hall, pp. 168-181, 1993.
    • (1993) Artificial Intelligence Frontiers in Statistics , pp. 168-181
    • Esposito, F.1    Malerba, D.2    Semeraro, G.3
  • 12
    • 0003024008 scopus 로고
    • On the handling of continuous-valued attributes in decision tree generation
    • U.M. Fayyad and K.B. Irani. On the handling of continuous-valued attributes in decision tree generation. Machine Learning, vol. 8, pp. 87-102,1992.
    • (1992) Machine Learning , vol.8 , pp. 87-102
    • Fayyad, U.M.1    Irani, K.B.2
  • 13
    • 0025725152 scopus 로고
    • Rigel: An inductive learning system
    • R. Gemello, F. Mana, and L. Saitta. Rigel: An inductive learning system. Machine Learning, vol. 6, no. 1, pp. 7-35, 1991.
    • (1991) Machine Learning , vol.6 , Issue.1 , pp. 7-35
    • Gemello, R.1    Mana, F.2    Saitta, L.3
  • 14
    • 2542455833 scopus 로고
    • Learning conjunctive concepts in structural domains
    • D. Haussler. Learning conjunctive concepts in structural domains. Machine Learning, col. 4, no. 1, pp. 7-40,1989.
    • (1989) Machine Learning , vol.4 , Issue.1 , pp. 7-40
    • Haussler, D.1
  • 15
    • 0342671268 scopus 로고
    • Inductive generalization: A logical framework
    • I. Bratko and N. Lavrae (Eds.), Sigma Press
    • N. Helft Inductive generalization: A logical framework. In I. Bratko and N. Lavrae (Eds.), Progress in Machine Learning - Proceedings of the EWSL87, Sigma Press, pp. 149-157, 1987.
    • (1987) Progress in Machine Learning - Proceedings of the EWSL87 , pp. 149-157
    • Helft, N.1
  • 16
    • 0022134381 scopus 로고
    • Office document architecture and office document interchange formats: Current status of international standardization
    • W. Horak. Office document architecture and office document interchange formats: current status of international standardization. IEEE Computer, vol. 18, no. 10, pp. 50-60,1985.
    • (1985) IEEE Computer , vol.18 , Issue.10 , pp. 50-60
    • Horak, W.1
  • 18
    • 0001953060 scopus 로고    scopus 로고
    • Handling imperfect data in inductive logic programming
    • L. De Raedt (Ed.), Amsterdam: IOS Press
    • N. Lavrac, S. Dzeroski, and L Bratko, Handling imperfect data in inductive logic programming. In L. De Raedt (Ed.), Advances in Inductive Logic Programming, Amsterdam: IOS Press, pp. 48-64,1996.
    • (1996) Advances in Inductive Logic Programming , pp. 48-64
    • Lavrac, N.1    Dzeroski, S.2    Bratko, L.3
  • 20
    • 0242274806 scopus 로고    scopus 로고
    • A multistrategy approach to learning multiple dependent concepts
    • C. Taylor and R. Nakhaeizadeh (Eds.), London: Wiley
    • D. Malerba, G. Semeraro, and F. Esposito. A multistrategy approach to learning multiple dependent concepts. In C. Taylor and R. Nakhaeizadeh (Eds.), Machine Learning and Statistics: The Interface, London: Wiley, pp. 87-106, 1997.
    • (1997) Machine Learning and Statistics: The Interface , pp. 87-106
    • Malerba, D.1    Semeraro, G.2    Esposito, F.3
  • 22
    • 38149046441 scopus 로고
    • A prototype document image analysis system for technical journals
    • G. Nagy, S.C. Seth, and S.D. Stoddard. A prototype document image analysis system for technical journals. IEEE Computer, vol. 25, no. 7, pp. 10-22,1992.
    • (1992) IEEE Computer , vol.25 , Issue.7 , pp. 10-22
    • Nagy, G.1    Seth, S.C.2    Stoddard, S.D.3
  • 24
    • 8844261754 scopus 로고
    • The utility of knowledge in inductive learning
    • M.J. Pazzani, & D. Kibler. The utility of knowledge in inductive learning. Machine Learning, vol. 9, no. 1, pp. 57-94,1992.
    • (1992) Machine Learning , vol.9 , Issue.1 , pp. 57-94
    • Pazzani, M.J.1    Kibler, D.2
  • 26
    • 33744584654 scopus 로고
    • Induction of decision trees
    • R. Quinlan. Induction of decision trees. Machine Learning, vol. 1, pp. 81-106, 1986.
    • (1986) Machine Learning , vol.1 , pp. 81-106
    • Quinlan, R.1
  • 28
    • 84934555448 scopus 로고
    • Flattening and saturation: Two representation changes for generalization
    • C. Rouveirol. Flattening and saturation: Two representation changes for generalization. Machine Learning, vol. 14, pp. 219-232,1994.
    • (1994) Machine Learning , vol.14 , pp. 219-232
    • Rouveirol, C.1
  • 29
    • 84949198319 scopus 로고    scopus 로고
    • Ideal refinement of Datalog programs
    • M. Proietti (Ed.), LNCS 1048, Berlin Springer- Verlag
    • G. Semeraro, F. Esposito, and D. Malerba. Ideal refinement of Datalog programs. In M. Proietti (Ed.), Logic Program Synthesis and Transformation, LNCS 1048, Berlin Springer- Verlag, pp. 120-136,1996.
    • (1996) Logic Program Synthesis and Transformation , pp. 120-136
    • Semeraro, G.1    Esposito, F.2    Malerba, D.3
  • 31
    • 0021518106 scopus 로고
    • A theory of the learnable
    • L.G. Valiant A theory of the learnable. Communications of the ACM, vol. 27, no. 11, pp. 1134-1142, 1984.
    • (1984) Communications of the ACM , vol.27 , Issue.11 , pp. 1134-1142
    • Valiant, L.G.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.