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Volumn , Issue , 2009, Pages 76-87

A data mining ontology for algorithm selection and meta-mining

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COST FUNCTIONS; DATA HANDLING; DATA MINING; LEARNING SYSTEMS; OPTIMIZATION; PARAMETER ESTIMATION;

EID: 84867653110     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (65)

References (28)
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    • Toward intelligent assistance for a data mining process: An ontology-based approach for cost-sensitive classification
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    • Bernstein, A.1    Provost, F.2    Hill, S.3
  • 12
    • 29644438050 scopus 로고    scopus 로고
    • Statistical comparisons of classifiers over multiple data sets
    • J. Demsar. Statistical comparisons of classifiers over multiple data sets. Journal of Machine Learning Research, 7:1-30, 2006.
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    • Demsar, J.1
  • 15
    • 0000468432 scopus 로고
    • Estimating continuous distributions in Bayesian classifiers
    • P. Besnard and S. Hanks, editors. Morgan Kaufmann
    • G. H. John and P. Langley. Estimating continuous distributions in bayesian classifiers. In P. Besnard and S. Hanks, editors, Procs. Eleventh Conference on Uncertainty in Artificial Intelligence, pages 338-345. Morgan Kaufmann, 1995.
    • (1995) Procs. Eleventh Conference on Uncertainty in Artificial Intelligence , pp. 338-345
    • John, G.H.1    Langley, P.2
  • 18
    • 0034274591 scopus 로고    scopus 로고
    • A comparison of prediction accuracy, complexity, and training time of thirty-three old and new classification algorithms
    • T. Lim, W. Loh, and Y. Shih. A comparison of prediction accuracy, complexity, and training time of thirty-three old and new classification algorithms. Machine Learning, 40:35-75, 2000.
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    • Lim, T.1    Loh, W.2    Shih, Y.3
  • 22
    • 0000606355 scopus 로고
    • Empirical learning as a function of concept character
    • L. Rendell and E. Cho. Empirical learning as a function of concept character. Machine Learning, 5:267-298, 1990.
    • (1990) Machine Learning , vol.5 , pp. 267-298
    • Rendell, L.1    Cho, E.2
  • 23
    • 0003056605 scopus 로고
    • The algorithm selection problem
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    • Rice, J.1
  • 24
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    • Cross-disciplinary perspectives on meta-learning for algorithm selection
    • K. A. Smith-Miles. Cross-disciplinary perspectives on meta-learning for algorithm selection. ACM Computing Surveys, 41(1), 2008.
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    • Smith-Miles, K.A.1
  • 26
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    • The lack of a priori distinctions between learning algorithms
    • D. Wolpert. The lack of a priori distinctions between learning algorithms. Neural Computation, 8(7):1381-1390, 1996.
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    • Wolpert, D.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.