{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T11:58:23Z","timestamp":1753358303041},"reference-count":31,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2015,7,14]],"date-time":"2015-07-14T00:00:00Z","timestamp":1436832000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Data Min Knowl Disc"],"published-print":{"date-parts":[[2016,5]]},"DOI":"10.1007\/s10618-015-0429-7","type":"journal-article","created":{"date-parts":[[2015,7,13]],"date-time":"2015-07-13T05:53:27Z","timestamp":1436766807000},"page":"576-604","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Parameter learning in hybrid Bayesian networks using prior knowledge"],"prefix":"10.1007","volume":"30","author":[{"given":"Inmaculada","family":"P\u00e9rez-Bernab\u00e9","sequence":"first","affiliation":[]},{"given":"Antonio","family":"Fern\u00e1ndez","sequence":"additional","affiliation":[]},{"given":"Rafael","family":"Rum\u00ed","sequence":"additional","affiliation":[]},{"given":"Antonio","family":"Salmer\u00f3n","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2015,7,14]]},"reference":[{"key":"429_CR1","doi-asserted-by":"crossref","first-page":"1630","DOI":"10.1016\/j.envsoft.2010.04.016","volume":"25","author":"PA Aguilera","year":"2010","unstructured":"Aguilera PA, Fern\u00e1ndez A, Reche F, Rum\u00ed R (2010) Hybrid Bayesian network classifiers: application to species distribution models. Environ Model Softw 25:1630\u20131639","journal-title":"Environ Model Softw"},{"key":"429_CR2","first-page":"255","volume":"17","author":"J Alcal\u00e1-Fdez","year":"2011","unstructured":"Alcal\u00e1-Fdez J, Fernandez A, Luengo J, Derrac J, Garc\u00eda S, S\u00e1nchez L, Herrera F (2011) Keel data-mining software tool: data set repository, integration of algorithms and experimental analysis framework. J Mult Valued Logic Soft Comput 17:255\u2013287","journal-title":"J Mult Valued Logic Soft Comput"},{"key":"429_CR3","unstructured":"Bache K, Lichman M (2013) UCI machine learning repository. http:\/\/archive.ics.uci.edu\/ml"},{"key":"429_CR4","volume-title":"Bayesian theory","author":"JM Bernardo","year":"2009","unstructured":"Bernardo JM, Smith AF (2009) Bayesian theory, vol 405. Wiley, New York"},{"issue":"2","key":"429_CR5","first-page":"187","volume":"19","author":"R Clemen","year":"1999","unstructured":"Clemen R, Winkler R (1999) Combining probability distributions from experts in risk analysis. Risk Anal 19(2):187\u2013203","journal-title":"Risk Anal"},{"key":"429_CR6","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1007\/s13748-014-0048-3","volume":"2","author":"A Fern\u00e1ndez","year":"2014","unstructured":"Fern\u00e1ndez A, G\u00e1mez JA, Rum\u00ed R, Salmer\u00f3n A (2014) Data clustering using hidden variables in hybrid Bayesian networks. Prog Artif Intell 2:141\u2013152","journal-title":"Prog Artif Intell"},{"key":"429_CR7","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1142\/S0218488510006398","volume":"18","author":"A Fern\u00e1ndez","year":"2010","unstructured":"Fern\u00e1ndez A, Nielsen JD, Salmer\u00f3n A (2010) Learning Bayesian networks for regression from incomplete databases. Int J Uncertain Fuzziness Knowl Based Syst 18:69\u201386","journal-title":"Int J Uncertain Fuzziness Knowl Based Syst"},{"key":"429_CR8","unstructured":"Fern\u00e1ndez A, P\u00e9rez-Bernab\u00e9 I, Rum\u00ed R, Salmer\u00f3n A (2013) Incorporating prior knowledge when learning mixtures of truncated basis functions from data. In: Jaeger M, Nielsen TD, Viappiani P (eds) Proceedings of the 12th Scandinavian AI conference (SCAI\u20192013) pp 95\u2013104"},{"key":"429_CR9","doi-asserted-by":"crossref","unstructured":"Fern\u00e1ndez A, P\u00e9rez-Bernab\u00e9 I, Salmer\u00f3n A (2013) On using the PC algorithm for learning continuous Bayesian networks: an Experimental Analysis. In: Proceedings of the 15th conference of the Spanish Association for Artificial Intelligence (CAEPIA\u20192013). Lecture Notes in Computer Science, vol 8109. Springer, Berlin, pp 342\u2013351","DOI":"10.1007\/978-3-642-40643-0_35"},{"key":"429_CR10","doi-asserted-by":"crossref","unstructured":"Fern\u00e1ndez A, Rum\u00ed R, del Sagrado J, Salmer\u00f3n A (2014) Supervised classification using hybrid probabilistic decision graphs. In: Proceedings of the 7th European workshop on probabilistic graphical models (PGM\u20192014). Lecture Notes in Artificial Intelligence, vol 8754. Springer, Berlin, pp 206\u2013221","DOI":"10.1007\/978-3-319-11433-0_14"},{"key":"429_CR11","doi-asserted-by":"crossref","unstructured":"Flores J, G\u00e1mez JA, Mart\u00ednez AM, Salmer\u00f3n A (2011) Mixtures of truncated exponentials in supervised classification: case study for the naive Bayes and averaged one-dependence estimators. In: Ventura S, Abraham A, Cios KJ, Romero C, Marcelloni F, Ben\u00edtez JM, Gibaja EL (eds) Proceedings of the 11th international conference on intelligent systems design and applications (ISDA\u20192011), pp 593\u2013598","DOI":"10.1109\/ISDA.2011.6121720"},{"key":"429_CR12","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1023\/A:1009730122752","volume":"1","author":"D Heckerman","year":"1997","unstructured":"Heckerman D (1997) Bayesian networks for data mining. Data Min Knowl Discov 1:79\u2013119","journal-title":"Data Min Knowl Discov"},{"key":"429_CR13","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1016\/j.inffus.2011.11.004","volume":"14","author":"T Kanamori","year":"2013","unstructured":"Kanamori T, Takenouchi T (2013) Improving Logitboost with prior knowledge. Inf Fusion 14:208\u2013219","journal-title":"Inf Fusion"},{"key":"429_CR14","doi-asserted-by":"crossref","first-page":"940","DOI":"10.1016\/j.ijar.2013.09.012","volume":"55","author":"H Langseth","year":"2014","unstructured":"Langseth H, Nielsen T, P\u00e9rez-Bernab\u00e9 I, Salmer\u00f3n A (2014) Learning mixtures of truncated basis functions from data. Int J Approx Reason 55:940\u2013956","journal-title":"Int J Approx Reason"},{"key":"429_CR15","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1016\/j.ijar.2011.10.004","volume":"53","author":"H Langseth","year":"2012","unstructured":"Langseth H, Nielsen T, Rum\u00ed R, Salmer\u00f3n A (2012) Mixtures of truncated basis functions. Int J Approx Reason 53:212\u2013227","journal-title":"Int J Approx Reason"},{"key":"429_CR16","unstructured":"Langseth H, Nielsen T, Salmer\u00f3n A (2012) Learning mixtures of truncated basis functions from data. In: Cano A, G\u00f3mez-Olmedo M, Nielsen TD (eds) Proceedings of the 6th European workshop on probabilistic graphical models (PGM\u20192012), pp 163\u2013170"},{"key":"429_CR17","doi-asserted-by":"crossref","first-page":"1098","DOI":"10.1080\/01621459.1992.10476265","volume":"87","author":"S Lauritzen","year":"1992","unstructured":"Lauritzen S (1992) Propagation of probabilities, means and variances in mixed graphical association models. J Am Stat Assoc 87:1098\u20131108","journal-title":"J Am Stat Assoc"},{"key":"429_CR18","unstructured":"L\u00f3pez-Cruz PL, Bielza C, Larra\u00f1aga P (2012) Learning mixtures of polynomials from data using B-spline interpolation. In: Cano A, G\u00f3mez-Olmedo M, Nielsen TD (eds) Proceedings of the 6th European workshop on probabilistic graphical models (PGM\u201912), pp 211\u2013218"},{"key":"429_CR19","doi-asserted-by":"crossref","first-page":"989","DOI":"10.1016\/j.ijar.2013.09.018","volume":"55","author":"PL L\u00f3pez-Cruz","year":"2014","unstructured":"L\u00f3pez-Cruz PL, Bielza C, Larra\u00f1aga P (2014) Learning mixtures of polynomials of multidimensional probability densities from data using B-spline interpolation. Int J Approx Reason 55:989\u20131010","journal-title":"Int J Approx Reason"},{"key":"429_CR20","doi-asserted-by":"crossref","unstructured":"Luengo JC, Rum\u00ed R (2015) Naive Bayes classifier with mixtures of polynomials. In: De Marsico M, Figueiredo M, Fred A (eds) Proceedings of the 4th international conference on pattern recognition applications and methods (ICPRAM\u20192015), vol 1, pp 14\u201324","DOI":"10.5220\/0005166000140024"},{"key":"429_CR21","doi-asserted-by":"crossref","unstructured":"Moral S, Rum\u00ed R, Salmer\u00f3n A (2001) Mixtures of truncated exponentials in hybrid Bayesian networks. In: Proceedings of the 6th European conference on symbolic and quantitative approaches to reasoning with uncertainty (ECSQARU\u20192001). Lecture Notes in Artificial Intelligence, vol 2143, pp 135\u2013143","DOI":"10.1007\/3-540-44652-4_15"},{"key":"429_CR22","doi-asserted-by":"crossref","unstructured":"Moral S, Rum\u00ed R, Salmer\u00f3n A (2003) Approximating conditional MTE distributions by means of mixed trees. In: Proceedings of the 7th European conference on symbolic and quantitative approaches to reasoning with uncertainty (ECSQARU\u20192003). Lecture Notes in Artificial Intelligence, vol 2711, pp 173\u2013183","DOI":"10.1007\/978-3-540-45062-7_14"},{"key":"429_CR23","doi-asserted-by":"crossref","first-page":"697","DOI":"10.1142\/S0218488507004959","volume":"15","author":"M Morales","year":"2007","unstructured":"Morales M, Rodr\u00edguez C, Salmer\u00f3n A (2007) Selective naive Bayes for regression using mixtures of truncated exponentials. Int J Uncertain Fuzziness Knowl Based Syst 15:697\u2013716","journal-title":"Int J Uncertain Fuzziness Knowl Based Syst"},{"key":"429_CR24","volume-title":"Probabilistic reasoning in intelligent systems","author":"J Pearl","year":"1988","unstructured":"Pearl J (1988) Probabilistic reasoning in intelligent systems. Morgan-Kaufmann, San Mateo"},{"key":"429_CR25","unstructured":"R Development Core Team (2011) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. http:\/\/www.R-project.org\/ . ISBN 3-900051-07-0"},{"key":"429_CR26","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1007\/BF02607059","volume":"15","author":"R Rum\u00ed","year":"2006","unstructured":"Rum\u00ed R, Salmer\u00f3n A, Moral S (2006) Estimating mixtures of truncated exponentials in hybrid Bayesian networks. Test 15:397\u2013421","journal-title":"Test"},{"key":"429_CR27","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1214\/aos\/1176344136","volume":"6","author":"G Schwarz","year":"1978","unstructured":"Schwarz G (1978) Estimating the dimension of a model. Ann Stat 6:461\u2013464","journal-title":"Ann Stat"},{"key":"429_CR28","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1016\/B978-0-444-88650-7.50019-6","volume-title":"Uncertainty in artificial intelligence 4","author":"P Shenoy","year":"1990","unstructured":"Shenoy P, Shafer G (1990) Axioms for probability and belief function propagation. In: Shachter R, Levitt T, Lemmer J, Kanal L (eds) Uncertainty in artificial intelligence 4. North Holland, Amsterdam, pp 169\u2013198"},{"key":"429_CR29","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1016\/j.ijar.2010.09.003","volume":"52","author":"P Shenoy","year":"2011","unstructured":"Shenoy P, West J (2011) Inference in hybrid Bayesian networks using mixtures of polynomials. Int J Approx Reason 52:641\u2013657","journal-title":"Int J Approx Reason"},{"key":"429_CR30","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1007\/s10618-008-0101-6","volume":"18","author":"T Wong","year":"2009","unstructured":"Wong T (2009) Alternative prior assumptions for improving the performance of na\u00efve Bayesian classifiers. Data Min Knowl Discov 18:183\u2013213","journal-title":"Data Min Knowl Discov"},{"key":"429_CR31","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1613\/jair.305","volume":"5","author":"N Zhang","year":"1996","unstructured":"Zhang N, Poole D (1996) Exploiting causal independence in Bayesian network inference. J Artif Intell Res 5:301\u2013328","journal-title":"J Artif Intell Res"}],"container-title":["Data Mining and Knowledge Discovery"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10618-015-0429-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10618-015-0429-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10618-015-0429-7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,28]],"date-time":"2019-08-28T05:09:07Z","timestamp":1566968947000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10618-015-0429-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,7,14]]},"references-count":31,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2016,5]]}},"alternative-id":["429"],"URL":"https:\/\/doi.org\/10.1007\/s10618-015-0429-7","relation":{},"ISSN":["1384-5810","1573-756X"],"issn-type":[{"value":"1384-5810","type":"print"},{"value":"1573-756X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,7,14]]}}}