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Volumn 6717 LNAI, Issue , 2011, Pages 194-205

Scaling up the greedy equivalence search algorithm by constraining the search space of equivalence classes

Author keywords

[No Author keywords available]

Indexed keywords

HIGH DIMENSIONALITY; ITS EFFICIENCIES; LEARNING BAYESIAN NETWORKS; MODIFIED ALGORITHMS; SCALING-UP; SEARCH ALGORITHMS; SEARCH SPACES; STATE-OF-THE-ART ALGORITHMS;

EID: 79960128832     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-22152-1_17     Document Type: Conference Paper
Times cited : (3)

References (10)
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    • Morgan Kaufmann Publishers Inc., San Francisco
    • Buntine, W.: Theory refinement on Bayesian networks. In: UAI 1991, pp. 52-60. Morgan Kaufmann Publishers Inc., San Francisco (1991)
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    • Buntine, W.1
  • 3
    • 0042967741 scopus 로고    scopus 로고
    • Optimal structure identification with greedy search
    • Chickering, D.: Optimal structure identification with greedy search. J. Mach. Learn. Res. 3, 507-554 (2002)
    • (2002) J. Mach. Learn. Res. , vol.3 , pp. 507-554
    • Chickering, D.1
  • 4
    • 0002157592 scopus 로고
    • Learning Bayesian networks: Search methods and experimental results
    • Chickering, D.M., Geiger, D., Heckerman, D.: Learning Bayesian networks: Search methods and experimental results. In: Proc. AISTATS 1995, pp. 112-128 (1995)
    • (1995) Proc. AISTATS 1995 , pp. 112-128
    • Chickering, D.M.1    Geiger, D.2    Heckerman, D.3
  • 5
    • 0002219642 scopus 로고    scopus 로고
    • Learning Bayesian network structure from massive datasets: The "sparse Candidate" algorithm
    • Friedman, N., Nachman, I., Pe'er, D.: Learning Bayesian network structure from massive datasets: The "Sparse Candidate" algorithm. In: UAI 1999, pp. 206-215 (1999)
    • (1999) UAI 1999 , pp. 206-215
    • Friedman, N.1    Nachman, I.2    Pe'er, D.3
  • 6
    • 78651369196 scopus 로고    scopus 로고
    • Learning Bayesian networks by hill climbing: Efficient methods based on progressive restriction of the neighborhood
    • doi:10.1007/s10618-010-0178-6 (to appear)
    • Gámez, J.A., Mateo, J.L., Puerta, J.M.: Learning Bayesian networks by hill climbing: efficient methods based on progressive restriction of the neighborhood. Data Min. Knowl. Disc. (2010), doi:10.1007/s10618-010-0178-6 (to appear)
    • (2010) Data Min. Knowl. Disc.
    • Gámez, J.A.1    Mateo, J.L.2    Puerta, J.M.3
  • 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. Mach. Learn. 20(3), 197-243 (1995)
    • (1995) Mach. Learn , vol.20 , Issue.3 , pp. 197-243
    • Heckerman, D.1    Geiger, D.2    Chickering, D.M.3
  • 10
    • 33746035971 scopus 로고    scopus 로고
    • The max-min hill-climbing Bayesian network structure learning algorithm
    • DOI 10.1007/s10994-006-6889-7
    • Tsamardinos, I., Brown, L.E., Aliferis, C.F.: The max-min hill-climbing Bayesian network structure learning algorithm. Mach. Learn. 65(1), 31-78 (2006) (Pubitemid 44451193)
    • (2006) Machine Learning , vol.65 , Issue.1 , pp. 31-78
    • Tsamardinos, I.1    Brown, L.E.2    Aliferis, C.F.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.