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Volumn , Issue , 2002, Pages 498-505

A hybrid approach to discover Bayesian networks from databases using evolutionary programming

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Indexed keywords


EID: 4444358530     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (26)

References (19)
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    • Cheng, J.1    Greiner, R.2    Kelly, J.3    Bell, D.4    Liu, W.5
  • 6
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    • Technical report, Microsoft Research, Advanced Technology Division, March
    • D. Heckerman. A tutorial on learning Bayesian networks. Technical report, Microsoft Research, Advanced Technology Division, March 1995.
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    • Heckerman, D.1
  • 7
    • 34249832377 scopus 로고
    • A Bayesian method for the induction of probabilistic networks from data
    • E. Herskovits and G. Cooper. A Bayesian method for the induction of probabilistic networks from data. Machine Learning, 9(4):309-347, 1992.
    • (1992) Machine Learning , vol.9 , Issue.4 , pp. 309-347
    • Herskovits, E.1    Cooper, G.2
  • 9
    • 0002610991 scopus 로고    scopus 로고
    • Learning augmented Bayesian classifiers: A comparison of distribution-based and classification-based approaches
    • D. Heckerman and J. Whittaker, editors, Fort Lauderdale, Florida, January Morgan Kaufmann
    • E. J. Keogh and M. J. Pazzani. Learning augmented Bayesian classifiers: A comparison of distribution-based and classification-based approaches. In D. Heckerman and J. Whittaker, editors, Proceedings of the Seventh International Workshop on A1 and Statistics, pages 225-230, Fort Lauderdale, Florida, January 1999. Morgan Kaufmann.
    • (1999) Proceedings of the Seventh International Workshop on A1 and Statistics , pp. 225-230
    • Keogh, E.J.1    Pazzani, M.J.2
  • 10
    • 0028482006 scopus 로고
    • Learning Bayesian belief networks-an approach based on the MDL principle
    • W. Lam and F. Bacchus. Learning Bayesian belief networks-an approach based on the MDL principle. Computational Intelligence, 10(4):269-293, 1994.
    • (1994) Computational Intelligence , vol.10 , Issue.4 , pp. 269-293
    • Lam, W.1    Bacchus, F.2
  • 18
    • 0033076357 scopus 로고    scopus 로고
    • Using evolutionary programming and minimum description length principle for data mining of Bayesian networks
    • February
    • M. L. Wong, W. Lam, and K. S. Leung. Using evolutionary programming and minimum description length principle for data mining of Bayesian networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 21(2):174-178, February 1999.
    • (1999) IEEE Transactions on Pattern Analysis and Machine Intelligence , vol.21 , Issue.2 , pp. 174-178
    • Wong, M.L.1    Lam, W.2    Leung, K.S.3
  • 19
    • 0002082928 scopus 로고    scopus 로고
    • Issues and problems in applying neural computing to target marketing
    • J. Zahavi and N. Levin. Issues and problems in applying neural computing to target marketing. Journal of Direct Marketing, 11(4):63-75, 1997.
    • (1997) Journal of Direct Marketing , vol.11 , Issue.4 , pp. 63-75
    • Zahavi, J.1    Levin, N.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.