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Volumn 4632 LNAI, Issue , 2007, Pages 454-465

Bayesian network structure ensemble learning

Author keywords

[No Author keywords available]

Indexed keywords

LEARNING SYSTEMS; MATHEMATICAL MODELS; DATA MINING; MODEL STRUCTURES;

EID: 38049003768     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-73871-8_42     Document Type: Conference Paper
Times cited : (9)

References (16)
  • 1
    • 0036567524 scopus 로고    scopus 로고
    • Learning Belief Networks form Data: An Information Theory Based Approach
    • Cheng, J., Greiner, R., Kelly, J., Bell, D., Liu, W.: Learning Belief Networks form Data: An Information Theory Based Approach. Artificial Intelligence 137(1-2), 43-90 (2002)
    • (2002) Artificial Intelligence , vol.137 , Issue.1-2 , pp. 43-90
    • Cheng, J.1    Greiner, R.2    Kelly, J.3    Bell, D.4    Liu, W.5
  • 3
    • 0031361611 scopus 로고    scopus 로고
    • Machine Learning Research: Four Current Directions
    • Dietterich, T.G.: Machine Learning Research: Four Current Directions. AI Magazine 18(4), 745-770 (1997)
    • (1997) AI Magazine , vol.18 , Issue.4 , pp. 745-770
    • Dietterich, T.G.1
  • 7
    • 34249761849 scopus 로고
    • Learning Bayesian Networks: The Combination of Knowledge and Statistical Data
    • Heckerman, D., Geiger, D., Chickering, D.M.: Learning Bayesian Networks: the Combination of Knowledge and Statistical Data. Machine Learning 20(3), 197-243 (1995)
    • (1995) Machine Learning , vol.20 , Issue.3 , pp. 197-243
    • Heckerman, D.1    Geiger, D.2    Chickering, D.M.3
  • 8
    • 38049078994 scopus 로고    scopus 로고
    • Learning Bayesian Network: Search Methods and Experimental Results
    • Fisher, D, Lenz, H, eds, Learning from Data: Artificial Intelligence and Statistics, 112, Springer, New York
    • Chickering, D.M., Heckerman, D., Geiger, D.: Learning Bayesian Network: Search Methods and Experimental Results. In: Fisher, D., Lenz, H. (eds.): Learning from Data: Artificial Intelligence and Statistics 5, Lecture Notes in Statistics 112, 143-153. Springer, New York (1996)
    • (1996) Lecture Notes in Statistics , vol.5 , pp. 143-153
    • Chickering, D.M.1    Heckerman, D.2    Geiger, D.3
  • 9
    • 1942452317 scopus 로고    scopus 로고
    • Optimal Reinsertion: A New Search Operator for Accelerated and More Accurate Bayesian Network Structure Learning
    • Fawcett, T, Mishra, N, eds, AAAI Press, Washington DC
    • Moore, A.W., Wong, W.K.: Optimal Reinsertion: A New Search Operator for Accelerated and More Accurate Bayesian Network Structure Learning. In: Fawcett, T., Mishra, N. (eds.) ICML 2003 - Machine Learning. Proceedings of the Twentieth International Conference, pp. 552-559. AAAI Press, Washington DC (2003)
    • (2003) ICML 2003 - Machine Learning. Proceedings of the Twentieth International Conference , pp. 552-559
    • Moore, A.W.1    Wong, W.K.2
  • 12
    • 38049050904 scopus 로고    scopus 로고
    • Recursive Autonomy Identification for Bayesian Network Structure Learning
    • Cowell, R.G, Ghahramani, Z, eds, Society for Artificial Intelligence and Statistics, London
    • Yehezkel, R., Lerner, B.: Recursive Autonomy Identification for Bayesian Network Structure Learning. In: Cowell, R.G., Ghahramani, Z. (eds.) AISTATS05. Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, pp. 429-436. Society for Artificial Intelligence and Statistics, London (2005)
    • (2005) AISTATS05. Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics , pp. 429-436
    • Yehezkel, R.1    Lerner, B.2
  • 16
    • 18144442687 scopus 로고    scopus 로고
    • Inferring Subnetworks from Perturbed Expression Profiles
    • Pe'er, D., Regev, A., Elidan, G., Friedman, N.: Inferring Subnetworks from Perturbed Expression Profiles. Bioinformatics 17(Suppl. 1), 1-9 (2001)
    • (2001) Bioinformatics , vol.17 , Issue.SUPPL. 1 , pp. 1-9
    • Pe'er, D.1    Regev, A.2    Elidan, G.3    Friedman, N.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.