메뉴 건너뛰기




Volumn , Issue , 1997, Pages 239-242

Scaling Up Inductive Algorithms: An Overview

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE;

EID: 0001326825     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (12)

References (12)
  • 1
    • 0003637516 scopus 로고
    • Ph.D. diss., School of Computer Science, University of Technology, Sydney, Australia
    • Buntine, W. 1991. A theory of learning classification rules. Ph.D. diss., School of Computer Science, University of Technology, Sydney, Australia.
    • (1991) A theory of learning classification rules
    • Buntine, W.1
  • 3
    • 85130734369 scopus 로고    scopus 로고
    • Knowledge Discovery and Data Mining: Towards a Unifying Framework
    • AAAI Press
    • Fayyad, U., Piatetsky-Shapiro, G., and Smyth, P. 1996. Knowledge Discovery and Data Mining: Towards a Unifying Framework. In Proc. KDD-96, 82-88. AAAI Press.
    • (1996) Proc. KDD-96 , pp. 82-88
    • Fayyad, U.1    Piatetsky-Shapiro, G.2    Smyth, P.3
  • 4
    • 0024082469 scopus 로고
    • Quantifying inductive bias: AI learning algorithms and Valiant's learning framework
    • Haussler, D. 1988. Quantifying inductive bias: AI learning algorithms and Valiant's learning framework. Artificial Intelligence, 36, 177-221.
    • (1988) Artificial Intelligence , vol.36 , pp. 177-221
    • Haussler, D.1
  • 5
    • 0027580356 scopus 로고
    • Very Simple Classification Rules Perform Well on Most Commonly Used Datasets
    • Holte, R.C. 1993. Very Simple Classification Rules Perform Well on Most Commonly Used Datasets. Machine Learning, 3, 63-91.
    • (1993) Machine Learning , vol.3 , pp. 63-91
    • Holte, R.C.1
  • 6
    • 0001863844 scopus 로고
    • Feature subset selection using wrapper model: Overfitting and dynamic search space topology
    • Kohavi, R. and Sommerfield, D. 1995. Feature subset selection using wrapper model: Overfitting and dynamic search space topology. In Proc. KDD-95.
    • (1995) Proc. KDD-95
    • Kohavi, R.1    Sommerfield, D.2
  • 7
    • 0000531852 scopus 로고
    • Generalization as search
    • Mitchell, T.M. 1982. Generalization as search. In Artificial Intelligence, 18(2), 203-226.
    • (1982) Artificial Intelligence , vol.18 , Issue.2 , pp. 203-226
    • Mitchell, T.M.1
  • 8
    • 0030127467 scopus 로고    scopus 로고
    • Scaling up inductive learning with massive parallelism
    • Provost, F.J. and Aronis, J.M. 1996. Scaling up inductive learning with massive parallelism. Machine Learning, 23, 33-46.
    • (1996) Machine Learning , vol.23 , pp. 33-46
    • Provost, F.J.1    Aronis, J.M.2
  • 9
    • 0001834468 scopus 로고
    • Inductive Policy: The pragmatics of bias selection
    • Provost, F.J. and Buchanan, B.G. 1995. Inductive Policy: The pragmatics of bias selection. Machine Learning, 20, 35-61.
    • (1995) Machine Learning , vol.20 , pp. 35-61
    • Provost, F.J.1    Buchanan, B.G.2
  • 12
    • 0002275318 scopus 로고
    • Problem solving and rule induction: A unified view
    • June 1996. and, Gregg (ed), New Jersey: Lawrence Erlbaum Associates
    • Montreal, Canada, June 1996. Simon, H. A. and Lea, G. 1973. Problem solving and rule induction: A unified view. In Gregg (ed.), Knowledge and Cognition, 105-127. New Jersey: Lawrence Erlbaum Associates.
    • (1973) Knowledge and Cognition , pp. 105-127
    • Montreal, Canada1    Simon, H. A.2    Lea, G.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.