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Volumn 8109 LNAI, Issue , 2013, Pages 310-320

Learning more accurate Bayesian networks in the CHC approach by adjusting the trade-off between efficiency and accuracy

Author keywords

Bayesian Networks; Constrained Search; Local Search; Machine Learning; Scalability

Indexed keywords

CONSTRAINED SEARCH; EXPERIMENTAL EVALUATION; HIGH-DIMENSIONAL; LEARNING BAYESIAN NETWORKS; LEARNING MODELS; LOCAL SEARCH; LOCAL SEARCH ALGORITHM; SEARCH PROCESS;

EID: 84885057502     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-40643-0_32     Document Type: Conference Paper
Times cited : (1)

References (10)
  • 2
    • 0001019707 scopus 로고    scopus 로고
    • Learning bayesian networks is NP-complete
    • Springer
    • Chickering, D.M.: Learning bayesian networks is NP-complete. In: Learning from data, pp. 121-130. Springer (1996)
    • (1996) Learning from Data , pp. 121-130
    • Chickering, D.M.1
  • 3
    • 78651369196 scopus 로고    scopus 로고
    • Learning bayesian networks by hill climbing: Efficient methods based on progressive restriction of the neighborhood
    • Gámez, J., Mateo, J., Puerta, J.: Learning bayesian networks by hill climbing: efficient methods based on progressive restriction of the neighborhood. Data Mining and Knowledge Discovery 22(1-2), 106-148 (2011)
    • (2011) Data Mining and Knowledge Discovery , vol.22 , Issue.1-2 , pp. 106-148
    • Gámez, J.1    Mateo, J.2    Puerta, J.3
  • 4
    • 84962258235 scopus 로고    scopus 로고
    • One iteration CHC algorithm for learning Bayesian networks: An effective and efficient algorithm for high dimensional problems
    • Gámez, J., Mateo, J., Puerta, J.: One iteration CHC algorithm for learning Bayesian networks: an effective and efficient algorithm for high dimensional problems. Progress in Artificial Intelligence 1(4), 329-346 (2012)
    • (2012) Progress in Artificial Intelligence , vol.1 , Issue.4 , pp. 329-346
    • Gámez, J.1    Mateo, J.2    Puerta, J.3
  • 6
    • 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) (1995)
    • (1995) Machine Learning , vol.20 , Issue.3
    • 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
    • Tsamardinos, I., Brown, L., Aliferis, C.: The max-min hill-climbing bayesian network structure learning algorithm. Machine Learning 65(1), 31-78 (2006)
    • (2006) Machine Learning , vol.65 , Issue.1 , pp. 31-78
    • Tsamardinos, I.1    Brown, L.2    Aliferis, C.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.