메뉴 건너뛰기




Volumn 20, Issue 5, 2008, Pages 628-640

Improving bayesian network structure learning with mutual information-based node ordering in the K2 algorithm

Author keywords

Classification; Data mining; Machine learning

Indexed keywords

BAYESIAN NETWORK STRUCTURE; CLASSIFICATION; COMPLEX NETWORKS; FUNCTION-BASED APPROACH; HARD TASK; K2 ALGORITHM; LEARNING STRUCTURE; MACHINE LEARNING; MUTUAL INFORMATIONS; NETWORK DATA; NODE ORDERING; STRUCTURE-LEARNING;

EID: 70350314967     PISSN: 10414347     EISSN: None     Source Type: Journal    
DOI: 10.1109/TKDE.2007.190732     Document Type: Article
Times cited : (154)

References (48)
  • 2
    • 33750253118 scopus 로고    scopus 로고
    • A Probabilistic Framework for Dialog Simulation and Optimal Strategy Learning
    • O. Pietquin and T. Dutoit, "A Probabilistic Framework for Dialog Simulation and Optimal Strategy Learning," IEEE Trans. Speech and Audio Processing, vol.14, no.2, pp. 589-599, 2005.
    • (2005) IEEE Trans. Speech and Audio Processing , vol.14 , Issue.2 , pp. 589-599
    • Pietquin, O.1    Dutoit, T.2
  • 3
    • 24044458805 scopus 로고
    • The structure of bayes networks for visual recognition
    • T.L.R. Shacter, L.N. Kanal, and J.F. Lemmer, eds.
    • J. Agosta, "The Structure of Bayes Networks for Visual Recognition," Uncertainty in Artificial Intelligence, T.L.R. Shacter, L.N. Kanal, and J.F. Lemmer, eds., vol.4, pp. 397-405, 1990.
    • (1990) Uncertainty in Artificial Intelligence , vol.4 , pp. 397-405
    • Agosta, J.1
  • 4
    • 84987031663 scopus 로고
    • Probabilistic similarity networks
    • D. Heckerman, "Probabilistic Similarity Networks," Networks, vol.20, pp. 607-636, 1990.
    • (1990) Networks , vol.20 , pp. 607-636
    • Heckerman, D.1
  • 5
    • 0034215972 scopus 로고    scopus 로고
    • Constructing bayesian networks for medical diagnosis from incomplete and partially correct statistics
    • D. Nikovski, "Constructing Bayesian Networks for Medical Diagnosis from Incomplete and Partially Correct Statistics," IEEE Trans. Knowledge and Data Eng., vol.12, pp. 509-516, 2000.
    • (2000) IEEE Trans. Knowledge and Data Eng. , vol.12 , pp. 509-516
    • Nikovski, D.1
  • 6
    • 0033707946 scopus 로고    scopus 로고
    • Using Bayesian networks to analyze expression data
    • DOI 10.1089/106652700750050961
    • N. Friedman, M. Linial, I. Nachman, and D. Pe'er, "Using Bayesian Networks to Analyze Expression Data," J. Computational Biology, vol.7, pp. 601-620, 2000. (Pubitemid 30944025)
    • (2000) Journal of Computational Biology , vol.7 , Issue.3-4 , pp. 601-620
    • Friedman, N.1    Linial, M.2    Nachman, I.3    Pe'er, D.4
  • 7
    • 12344259602 scopus 로고    scopus 로고
    • Advances to bayesian network inference for generating causal networks from observational biological data
    • J. Yu, V. Smith, P. Wang, A. Hartemink, and E. Jarvis, "Advances to Bayesian Network Inference for Generating Causal Networks from Observational Biological Data," Bioinformatics, vol.20, pp. 3594-3603, 2004.
    • (2004) Bioinformatics , vol.20 , pp. 3594-3603
    • Yu, J.1    Smith, V.2    Wang, P.3    Hartemink, A.4    Jarvis, E.5
  • 8
    • 0542396542 scopus 로고    scopus 로고
    • Independency relationships and learning algorithms for singly connected networks
    • L. de Campos, "Independency Relationships and Learning Algorithms for Singly Connected Networks," J. Experimental and Theoretical Artificial Intelligence, vol.10, pp. 511-549, 1998. (Pubitemid 128475478)
    • (1998) Journal of Experimental and Theoretical Artificial Intelligence , vol.10 , Issue.4 , pp. 511-549
    • De Campos, L.M.1
  • 9
    • 0034174383 scopus 로고    scopus 로고
    • A New Approach for Learning Belief Networks Using Independence Criteria
    • L. de Campos and J. Huete, "A New Approach for Learning Belief Networks Using Independence Criteria," Int'l J. Approximate Reasoning, vol.24, pp. 11-37, 2000.
    • (2000) Int'l J. Approximate Reasoning , vol.24 , pp. 11-37
    • De Campos, L.1    Huete, J.2
  • 11
    • 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, vol.10, pp. 269-293, 1994.
    • (1994) Computational Intelligence , vol.10 , pp. 269-293
    • Lam, W.1    Bacchus, F.2
  • 12
    • 34249832377 scopus 로고
    • A Bayesian Method for the Induction of Probabilistic Networks from Data
    • G. Cooper and E. Herskovits, "A Bayesian Method for the Induction of Probabilistic Networks from Data," Machine Learning, vol.9, pp. 309-347, 1992.
    • (1992) Machine Learning , vol.9 , pp. 309-347
    • Cooper, G.1    Herskovits, E.2
  • 13
    • 34249761849 scopus 로고
    • Learning bayesian networks: The combination of knowledge and statistical data
    • D. Heckerman, D. Geiger, and D. Chickering, "Learning Bayesian Networks: The Combination of Knowledge and Statistical Data," Machine Learning, vol.20, pp. 197-243, 1995.
    • (1995) Machine Learning , vol.20 , pp. 197-243
    • Heckerman, D.1    Geiger, D.2    Chickering, D.3
  • 15
    • 0000243504 scopus 로고
    • Graphical and recursive models for contingence tables
    • N. Wermuth and S. Lauritzen, "Graphical and Recursive Models for Contingence Tables," Biometrika, vol.72, pp. 537-552, 1983.
    • (1983) Biometrika , vol.72 , pp. 537-552
    • Wermuth, N.1    Lauritzen, S.2
  • 16
    • 0031185530 scopus 로고    scopus 로고
    • On the use of independence relationships for learning simplified brief networks
    • L. Campos and J. Huete, "On the Use of Independence Relationships for Learning Simplified Brief Networks," Int'l J. Intelligent Systems, vol.12, pp. 495-522, 1997.
    • (1997) Int'l J. Intelligent Systems , vol.12 , pp. 495-522
    • Campos, L.1    Huete, J.2
  • 22
    • 0042496103 scopus 로고    scopus 로고
    • Learning equivalence classes on bayesian-network structures
    • D. Chickering, "Learning Equivalence Classes on Bayesian-Network Structures," J. Machine Learning Research, vol.2, pp. 445-498, 2002.
    • (2002) J. Machine Learning Research , vol.2 , pp. 445-498
    • Chickering, D.1
  • 23
    • 0042967741 scopus 로고    scopus 로고
    • Optimal structure identification with greedy search
    • D. Chickering, "Optimal Structure Identification with Greedy Search," J. Machine Learning Research, vol.3, pp. 507-554, 2002.
    • (2002) J. Machine Learning Research , vol.3 , pp. 507-554
    • Chickering, D.1
  • 24
    • 0030124955 scopus 로고    scopus 로고
    • A guide to the literature on learning probabilistic networks from data
    • W. Buntine, "A Guide to the Literature on Learning Probabilistic Networks from Data," IEEE Trans. Knowledge and Data Eng., vol.8, pp. 195-210, 1996.
    • (1996) IEEE Trans. Knowledge and Data Eng. , vol.8 , pp. 195-210
    • Buntine, W.1
  • 25
    • 0037262841 scopus 로고    scopus 로고
    • Being bayesian about network structure: A bayesian approach to structure discovery in bayesian networks
    • N. Friedman and D. Koller, "Being Bayesian about Network Structure: A Bayesian Approach to Structure Discovery in Bayesian Networks," Machine Learning, vol.50, pp. 95-125, 2003.
    • (2003) Machine Learning , vol.50 , pp. 95-125
    • Friedman, N.1    Koller, D.2
  • 27
    • 0003021797 scopus 로고
    • A Construction of bayesian networks from databases based on an MDL principle
    • J. Suzuki, "A Construction of Bayesian Networks from Databases Based on an MDL Principle," Proc. Ninth Conf. Uncertainty in Artificial Intelligence, pp. 266-273, 1993.
    • (1993) Proc. Ninth Conf. Uncertainty in Artificial Intelligence , pp. 266-273
    • Suzuki, J.1
  • 28
    • 85017343247 scopus 로고
    • Belief networks construction using the minimum description length principle
    • R. Bouckaert, "Belief Networks Construction Using the Minimum Description Length Principle," Lecture Notes in Computer Science 747, pp. 41-48, 1993.
    • (1993) Lecture Notes in Computer Science , vol.747 , pp. 41-48
    • Bouckaert, R.1
  • 30
    • 84933530882 scopus 로고
    • Approximating discrete probability distributions with dependence trees
    • C. Chow and C. Liu, "Approximating Discrete Probability Distributions with Dependence Trees," IEEE Trans. Information Theory, vol.14, pp. 462-467, 1968.
    • (1968) IEEE Trans. Information Theory , vol.14 , pp. 462-467
    • Chow, C.1    Liu, C.2
  • 31
    • 31844439894 scopus 로고    scopus 로고
    • Exact bayesian structure discovery in bayesian networks
    • M. Koivisto and K. Sood, "Exact Bayesian Structure Discovery in Bayesian Networks," J. Machine Learning Research, vol.5, pp. 549-573, 2004.
    • (2004) J. Machine Learning Research , vol.5 , pp. 549-573
    • Koivisto, M.1    Sood, K.2
  • 32
    • 0001019707 scopus 로고    scopus 로고
    • Learning bayesian networks is np-complete
    • V, D. Fisher and H. Lenz, eds., Springer
    • D. Chickering, "Learning Bayesian Networks Is NP-Complete," Learning from Data: Artificial Intelligence and Statistics V, D. Fisher and H. Lenz, eds., pp. 121-130, Springer, 1996.
    • (1996) Learning from Data: Artificial Intelligence and Statistics , pp. 121-130
    • Chickering, D.1
  • 33
    • 33646107783 scopus 로고    scopus 로고
    • Large-sample learning of bayesian networks is NP-Hard
    • D. Chickering, D. Heckerman, and C. Meek, "Large-Sample Learning of Bayesian Networks Is NP-Hard," J. Machine Learning Research, vol.5, pp. 1287-1330, 2004.
    • (2004) J. Machine Learning Research , vol.5 , pp. 1287-1330
    • Chickering, D.1    Heckerman, D.2    Meek, C.3
  • 34
    • 21244484641 scopus 로고    scopus 로고
    • Searching for bayesian network structures in the space of restricted acyclic partially directed graphs
    • S. Acid and L. de Campos, "Searching for Bayesian Network Structures in the Space of Restricted Acyclic Partially Directed Graphs," J. Artificial Intelligence Research, vol.18, pp. 445-490, 2003.
    • (2003) J. Artificial Intelligence Research , vol.18 , pp. 445-490
    • Acid, S.1    De Campos, L.2
  • 35
    • 2542465947 scopus 로고    scopus 로고
    • On inclusion-driven learning of bayesian networks
    • R. Castelo and T. Kocka, "On Inclusion-Driven Learning of Bayesian Networks," J. Machine Learning Research, vol.4, pp. 527-574, 2003.
    • (2003) J. Machine Learning Research , vol.4 , pp. 527-574
    • Castelo, R.1    Kocka, T.2
  • 36
    • 0030192667 scopus 로고    scopus 로고
    • Learning bayesian network structures by searching for the best ordering with genetic algorithms
    • P. Larranaga, C. Kuijpers, R. Murga, and Y. Yurramendi, "Learning Bayesian Network Structures by Searching for the Best Ordering with Genetic Algorithms," IEEE Trans. Systems, Man, and Cybernetics, vol.26, pp. 487-493, 1996.
    • (1996) IEEE Trans. Systems, Man, and Cybernetics , vol.26 , pp. 487-493
    • Larranaga, P.1    Kuijpers, C.2    Murga, R.3    Yurramendi, Y.4
  • 39
    • 21844520724 scopus 로고
    • Bayesian graphical models for discrete data
    • D. Madigan and J. York, "Bayesian Graphical Models for Discrete Data," Int'l Statistical Rev., vol.63, pp. 215-232, 1995.
    • (1995) Int'l Statistical Rev. , vol.63 , pp. 215-232
    • Madigan, D.1    York, J.2
  • 40
    • 0004202337 scopus 로고    scopus 로고
    • An Introduction to Bayesian Networks
    • F. Jensen, An Introduction to Bayesian Networks. UCL Press, 1996.
    • (1996) UCL Press
    • Jensen, F.1
  • 43
    • 0001006209 scopus 로고
    • Local computations with probabilities on graphical structures and their application on expert systems
    • S. Lauritzen and D. Spiegelhalter, "Local Computations with Probabilities on Graphical Structures and Their Application on Expert Systems," J. Royal Statistical Soc., vol.50, pp. 157-224, 1988.
    • (1988) J. Royal Statistical Soc. , vol.50 , pp. 157-224
    • Lauritzen, S.1    Spiegelhalter, D.2
  • 46
    • 0036567524 scopus 로고    scopus 로고
    • Learning bayesian networks from data: An information-theory based approach
    • J. Cheng, R. Grenier, J. Kelly, D. Bell, and W. Liu, "Learning Bayesian Networks from Data: An Information-Theory Based Approach," Artificial Intelligence, vol.137, pp. 43-90, 2002.
    • (2002) Artificial Intelligence , vol.137 , pp. 43-90
    • Cheng, J.1    Grenier, R.2    Kelly, J.3    Bell, D.4    Liu, W.5
  • 47
    • 70350293646 scopus 로고    scopus 로고
    • http://bnt.sourceforge.net/, 2006.
    • (2006)


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.