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Volumn 2, Issue , 1999, Pages 714-719

Process-oriented estimation of generalization error

Author keywords

[No Author keywords available]

Indexed keywords

ADEQUATE MODELS; GENERALIZATION ERROR; OVERFITTING; PROCESS-ORIENTED; RULE INDUCTION; SEARCH PROCESS;

EID: 26944446739     PISSN: 10450823     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (9)

References (29)
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    • (1998) UCI Repository of Machine Learning Databases
    • Blake, C.1    Keogh, E.2    Merz, C.J.3
  • 4
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    • Brunk, C.1    Pazzani, M.J.2
  • 7
    • 0031272327 scopus 로고    scopus 로고
    • Efficient Approximations for the Marginal Likelihood of Bayesian Networks with Hidden Variables
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    • (1997) Machine Learning , vol.29 , Issue.2-3 , pp. 181-212
    • Chickering, D.M.1    Heckerman, D.2
  • 9
    • 34249966007 scopus 로고
    • The CN2 induction algorithm
    • P. Clark and T. Niblett. The CN2 induction algorithm. Machine Learning, 3:261-283, 1989.
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    • Clark, P.1    Niblett, T.2
  • 14
    • 85152635090 scopus 로고
    • An ounce of knowledge is worth a ton of data: Quantitative studies of the trade-off between expertise and data based on statistically well-founded empirical induction
    • Ithaca, NY, Morgan Kaufmann
    • B. R. Gaines. An ounce of knowledge is worth a ton of data: Quantitative studies of the trade-off between expertise and data based on statistically well-founded empirical induction. In Proceedings of the Sixth International Workshop on Machine Learning, pages 156-159, Ithaca, NY, 1989. Morgan Kaufmann.
    • (1989) Proceedings of the Sixth International Workshop on Machine Learning , pp. 156-159
    • Gaines, B.R.1
  • 16
    • 84880681405 scopus 로고    scopus 로고
    • Multiple comparisons in induction algorithms
    • To appear
    • D. Jensen and P. R. Cohen. Multiple comparisons in induction algorithms. Machine Learning, 1998. To appear.
    • (1998) Machine Learning
    • Jensen, D.1    Cohen, P.R.2
  • 21
    • 0000942050 scopus 로고
    • A theory and methodology of inductive learning
    • R. S. Michalski. A theory and methodology of inductive learning. Artificial Intelligence, 20:111-161, 1983.
    • (1983) Artificial Intelligence , vol.20 , pp. 111-161
    • Michalski, R.S.1
  • 23
    • 0025389210 scopus 로고
    • Boolean feature discovery in empirical learning
    • DOI 10.1023/A:1022611825350
    • G. Pagallo and D. Haussler. Boolean feature discovery in empirical learning. Machine Learning, 3:71-99, 1990. (Pubitemid 23621640)
    • (1990) Machine Learning , vol.5 , Issue.1 , pp. 71-99
    • Pagallo, G.1    Haussler, D.2
  • 26
    • 0018015137 scopus 로고
    • Modeling by shortest data description
    • J. Rissanen. Modeling by shortest data description. Automatica, 14:465-471, 1978.
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    • Rissanen, J.1
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    • M. Stone. Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society B, 36:111-147,1974.
    • (1974) Journal of the Royal Statistical Society B , vol.36 , pp. 111-147
    • Stone, M.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.