{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T05:02:46Z","timestamp":1784696566643,"version":"3.55.0"},"publisher-location":"Dordrecht","reference-count":38,"publisher":"Springer Netherlands","isbn-type":[{"value":"9789401061049","type":"print"},{"value":"9789401150149","type":"electronic"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[1998]]},"DOI":"10.1007\/978-94-011-5014-9_19","type":"book-chapter","created":{"date-parts":[[2012,7,29]],"date-time":"2012-07-29T00:48:48Z","timestamp":1343522928000},"page":"521-540","source":"Crossref","is-referenced-by-count":19,"title":["Learning Hybrid Bayesian Networks from Data"],"prefix":"10.1007","author":[{"given":"Stefano","family":"Monti","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gregory F.","family":"Cooper","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","reference":[{"key":"19_CR1","volume-title":"Adaptive probabilistic networks with hidden variables","author":"J Binder","year":"1997","unstructured":"J. Binder, D. Koller, S. Russel, and K. Kanazawa. Adaptive probabilistic networks with hidden variables. Machine Learning, 1997. To appear."},{"key":"19_CR2","series-title":"Technical Report NCRG\/4288, Neural Computing Research Group, Department of Computer Science","volume-title":"Mixture density networks","author":"C Bishop","year":"1994","unstructured":"C. Bishop. Mixture density networks. Technical Report NCRG\/4288, Neural Computing Research Group, Department of Computer Science, Aston University, Birmingham B4 7ET, U.K., February 1994."},{"key":"19_CR3","doi-asserted-by":"crossref","DOI":"10.1093\/oso\/9780198538493.001.0001","volume-title":"Neural Networks for Pattern Recognition","author":"C Bishop","year":"1995","unstructured":"C. Bishop. Neural Networks for Pattern Recognition. Oxford University Press, Oxford, 1995."},{"key":"19_CR4","first-page":"102","volume-title":"Proceedings of the 10th Conference of Uncertainty in Artificial Intelligence","author":"R Bouck\u00e6rt","year":"1994","unstructured":"R. Bouck\u00e6rt. Properties of learning algorithms for Bayesian belief networks. In Proceedings of the 10th Conference of Uncertainty in Artificial Intelligence, pages 102\u2013109, San Francisco, California, 1994. Morgan Kaufmann Publishers."},{"key":"19_CR5","volume-title":"Neuro-computing: Algorithms, Architectures and Applications","author":"J Bridle","year":"1989","unstructured":"J. Bridle. Probabilistic interpretation of feedforward classification network outputs, with relationships to statistical pattern recognition. In Neuro-computing: Algorithms, Architectures and Applications. Springer Verlag, New York, 1989."},{"key":"19_CR6","series-title":"IEEE Transactions on Knowledge and Data Engineering","volume-title":"A guide to the literature on learning probabilistic networks from data","author":"W Buntine","year":"1996","unstructured":"W. Buntine. A guide to the literature on learning probabilistic networks from data. IEEE Transactions on Knowledge and Data Engineering, 8(3), 1996."},{"key":"19_CR7","first-page":"52","volume-title":"Proceedings of the 7th Conference of Uncertainty in AI","author":"WL Buntine","year":"1991","unstructured":"W. L. Buntine. Theory refinement on Bayesian networks. In Proceedings of the 7th Conference of Uncertainty in AI, pages 52\u201360, 1991."},{"key":"19_CR8","volume-title":"Advances in Knowledge Discovery and Data Mining","author":"P Cheeseman","year":"1996","unstructured":"P. Cheeseman and J. Stutz. Bayesian classification (AutoClass): Theory and results. In U. M. Fayyad, G. Piatetsky-Shapiro, P. Smyth, and R. Uthurasamy, editors, Advances in Knowledge Discovery and Data Mining. MIT Press, 1996."},{"key":"19_CR9","first-page":"112","volume-title":"Proceedings of 5th Workshop on Artificial Intelligence and Statistics","author":"DM Chickering","year":"1995","unstructured":"D. M. Chickering, D. Geiger, and D. Heckerman. Learning Bayesian networks: search methods and experimental results. In Proceedings of 5th Workshop on Artificial Intelligence and Statistics, pages 112\u2013128, January 1995."},{"key":"19_CR10","volume-title":"Proceedings of the 12-th Conference of Uncertainty in AI","author":"DM Chickering","year":"1996","unstructured":"D. M. Chickering and D. Heckerman. Efficient approximation for the marginal likelihood of incomplete data given a Bayesian network. In Proceedings of the 12-th Conference of Uncertainty in AI, 1996."},{"key":"19_CR11","series-title":"Technical Report HPP-84\u201348, Dept. of Computer Science","volume-title":"NESTOR: A computer-based medical diagnostic that integrates causal and probabilistic knowledge","author":"GF Cooper","year":"1984","unstructured":"G. F. Cooper. NESTOR: A computer-based medical diagnostic that integrates causal and probabilistic knowledge. Technical Report HPP-84\u201348, Dept. of Computer Science, Stanford University, Palo Alto, California, 1984."},{"key":"19_CR12","first-page":"86","volume-title":"Proceedings of the 7th Conference of Uncertainty in Artificial Intelligence","author":"GF Cooper","year":"1991","unstructured":"G. F. Cooper and E. Herskovits. A Bayesian method for constructing Bayesian belief networks from databases. In Proceedings of the 7th Conference of Uncertainty in Artificial Intelligence, pages 86\u201394, Los Angeles, CA, 1991."},{"key":"19_CR13","first-page":"309","volume":"9","author":"GF Cooper","year":"1992","unstructured":"G. F. Cooper and E. Herskovits. A Bayesian Method for the Induction of Probabilistic Networks from Data. Machine Learning, 9: 309\u2013347, 1992.","journal-title":"Machine Learning"},{"key":"19_CR14","doi-asserted-by":"publisher","first-page":"278","DOI":"10.2307\/2981683","volume":"147","author":"A Dawid","year":"1984","unstructured":"A. Dawid. Present position and potential developments: Some personal views. Statistical theory. The prequential approach (with discussion). Journal of Royal Statistical Society A, 147: 278\u2013292, 1984.","journal-title":"Journal of Royal Statistical Society A"},{"key":"19_CR15","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1093\/oso\/9780198522669.003.0007","volume-title":"Bayesian Statistics 4","author":"A Dawid","year":"1992","unstructured":"A. Dawid. Prequential analysis, stochastic complexity and Bayesian inference. In J.M. Bernardo et al, editor, Bayesian Statistics 4, pages 109\u2013125. Oxford University Press, 1992."},{"key":"19_CR16","volume-title":"Building probabilistic networks: where do the numbers come from","year":"1995","unstructured":"M. Druzdzel, L. C. van der Gang, M. Henrion, and F. Jensen, editors. Building probabilistic networks: where do the numbers come from?, IJCAI-95 Workshop, Montreal, Qu\u00e9bec, 1995."},{"key":"19_CR17","doi-asserted-by":"publisher","DOI":"10.1007\/978-94-009-5897-5","volume-title":"Finite mixture distributions","author":"B Everitt","year":"1981","unstructured":"B. Everitt and D. Hand. Finite mixture distributions. Chapman and Hall, 1981."},{"key":"19_CR18","volume-title":"Proceedings of the First International Conference on Knowledge Discovery and Data Mining (KDD-95)","year":"1995","unstructured":"U. Fayyad and R. Uthurusamy, editors. Proceedings of the First International Conference on Knowledge Discovery and Data Mining (KDD-95), Montreal, Qu\u00e9bec, 1995. AAAI Press."},{"key":"19_CR19","first-page":"157","volume-title":"Proceedings of 13-th International Conference on Machine Learning","author":"N Friedman","year":"1996","unstructured":"N. Friedman and M. Goldszmidt. Discretization of continuous attributes while learning Bayesian networks. In L. Saitta, editor, Proceedings of 13-th International Conference on Machine Learning, pages 157\u2013165, 1996."},{"key":"19_CR20","volume-title":"Prooceedings of the 10th Conference of Uncertainty in AI","author":"D Geiger","year":"1994","unstructured":"D. Geiger and D. Heckerman. Learning Gaussian networks. In R. L. de Mantras and D. Poole, editors, Prooceedings of the 10th Conference of Uncertainty in AI, San Francisco, California, 1994. Morgan Kaufmann."},{"key":"19_CR21","volume-title":"Asymptotic model selection for directed networks with hidden variables","author":"D Geiger","year":"1996","unstructured":"D. Geiger, D. Heckerman, and C. Meek. Asymptotic model selection for directed networks with hidden variables. Technical Report MSR-TR-96\u201307, Microsoft Research, May 1996."},{"key":"19_CR22","volume-title":"Markov Chain Monte Carlo in Practice","author":"W Gilks","year":"1996","unstructured":"W. Gilks, S. Richardson, and D. Spiegelhalter. Markov Chain Monte Carlo in Practice. Chapman & Hall, 1996."},{"key":"19_CR23","first-page":"197","volume":"20","author":"D Heckerman","year":"1995","unstructured":"D. Heckerman, D. Geiger, and D. M. Chickering. Learning Bayesian networks: The combination of knowledge and statistical data. Machine Learning, 20: 197\u2013243, 1995.","journal-title":"Machine Learning"},{"key":"19_CR24","series-title":"Communications in Statistics - Theory and Methods","first-page":"25","volume-title":"Bayesian model averaging and model selection for Markov equivalence classes of acyclic digraphs","author":"D Madigan","year":"1996","unstructured":"D. Madigan, S. A. Andersson, M. D. Perlman, and C. T. Volinsky. Bayesian model averaging and model selection for Markov equivalence classes of acyclic digraphs. Communications in Statistics - Theory and Methods, 25, 1996."},{"key":"19_CR25","volume-title":"AAAI Workshop on Integrating Multiple Learned Models","author":"D Madigan","year":"1996","unstructured":"D. Madigan, A. E. Raftery, C. T. Volinsky, and J. A. Hoeting. Bayesian model averaging. In AAAI Workshop on Integrating Multiple Learned Models, 1996."},{"key":"19_CR26","series-title":"University of California, Irvine, Department of Information and Computer Science","volume-title":"Machine learning repository","author":"C Merz","year":"1996","unstructured":"C. Merz and P. Murphy. Machine learning repository. University of California, Irvine, Department of Information and Computer Science, 1996. http:\/\/www.ics.uci.edu\/mlearn\/MLRepository.html"},{"key":"19_CR27","doi-asserted-by":"publisher","first-page":"525","DOI":"10.1016\/S0893-6080(05)80056-5","volume":"6","author":"M Moller","year":"1993","unstructured":"M. Moller. A scaled conjugate gradient algorithm for fast supervised learning. Neural Networks, 6: 525\u2013533, 1993.","journal-title":"Neural Networks"},{"key":"19_CR28","volume-title":"Advances in Neural Information Processing Systems 9: Proceedings of the 1996 Conference","author":"S Monti","year":"1997","unstructured":"S. Monti and G. F. Cooper. Learning Bayesian belief networks with neural network estimators. In M. Mozer, M. Jordan, and T. Petsche, editors, Advances in Neural Information Processing Systems 9: Proceedings of the 1996 Conference, 1997."},{"key":"19_CR29","volume-title":"Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference","author":"J Pearl","year":"1988","unstructured":"J. Pearl. Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufman Publishers, Inc., 1988."},{"key":"19_CR30","series-title":"Sociological Methodology","first-page":"111","volume-title":"Bayesian model selection in social research (with discussion)","author":"AE Raftery","year":"1995","unstructured":"A. E. Raftery. Bayesian model selection in social research (with discussion). Sociological Methodology, pages 111\u2013196, 1995."},{"key":"19_CR31","unstructured":"A. E. Raftery. Hypothesis testing and model selection. In Gilks et al [22], chapter 10, pages 163\u2013188."},{"key":"19_CR32","doi-asserted-by":"publisher","first-page":"461","DOI":"10.1162\/neco.1991.3.4.461","volume":"3","author":"M Richard","year":"1991","unstructured":"M. Richard and R. Lippman. Neural network classifiers estimate Bayesian aposteriori probabilities. Neural Computation, 3: 461\u2013483, 1991.","journal-title":"Neural Computation"},{"key":"19_CR33","unstructured":"C. Robert. Mixtures of distributions: Inference and estimation. In Gilks et al [22], chapter 24, pages 441\u2013464."},{"key":"19_CR34","doi-asserted-by":"publisher","first-page":"461","DOI":"10.1214\/aos\/1176344136","volume":"6","author":"G Schwarz","year":"1996","unstructured":"G. Schwarz. Estimating the dimension of a model. Annals of Statistics, 6: 461\u2013464, 1996.","journal-title":"Annals of Statistics"},{"key":"19_CR35","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1016\/B978-0-444-70058-2.50032-2","volume-title":"Uncertainty in Artificial Intelligence 1","author":"R Shachter","year":"1986","unstructured":"R. Shachter. Intelligent probabilistic inference. In L. K.. J. Lemmer, editor, Uncertainty in Artificial Intelligence 1, pages 371\u2013382, Amsterdam, North-Holland, 1986."},{"issue":"3","key":"19_CR36","doi-asserted-by":"publisher","first-page":"219","DOI":"10.1214\/ss\/1177010888","volume":"8","author":"D Spiegelhalter","year":"1993","unstructured":"D. Spiegelhalter, A. Dawid, S. Lauritzen, and R. Cowell. Bayesian analysis in expert systems. Statistical Science, 8 (3): 219\u2013283, 1993.","journal-title":"Statistical Science"},{"key":"19_CR37","unstructured":"B. Thiesson. Accelerated quantification of Bayesian networks with incomplete data. In Fayyad and Uthurusamy [18], pages 306\u2013311."},{"key":"19_CR38","volume-title":"Statistical Analysis of Finite Mixture Distributions","author":"D Titterington","year":"1985","unstructured":"D. Titterington, A. Smith, and U. Makov. Statistical Analysis of Finite Mixture Distributions. Wiley, New York, 1985."}],"container-title":["Learning in Graphical Models"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-94-011-5014-9_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,4,27]],"date-time":"2024-04-27T22:40:12Z","timestamp":1714257612000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-94-011-5014-9_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[1998]]},"ISBN":["9789401061049","9789401150149"],"references-count":38,"URL":"https:\/\/doi.org\/10.1007\/978-94-011-5014-9_19","relation":{},"subject":[],"published":{"date-parts":[[1998]]}}}