{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,18]],"date-time":"2026-01-18T10:46:12Z","timestamp":1768733172368,"version":"3.49.0"},"reference-count":32,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2020,3,30]],"date-time":"2020-03-30T00:00:00Z","timestamp":1585526400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,3,30]],"date-time":"2020-03-30T00:00:00Z","timestamp":1585526400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100000923","name":"Australian Research Council","doi-asserted-by":"crossref","award":["DE170100037"],"award-info":[{"award-number":["DE170100037"]}],"id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100004543","name":"China Scholarship Council","doi-asserted-by":"publisher","award":["201506300081"],"award-info":[{"award-number":["201506300081"]}],"id":[{"id":"10.13039\/501100004543","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000923","name":"Australia Research Council","doi-asserted-by":"crossref","award":["DP190100017"],"award-info":[{"award-number":["DP190100017"]}],"id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Knowl Inf Syst"],"published-print":{"date-parts":[[2020,9]]},"DOI":"10.1007\/s10115-020-01458-z","type":"journal-article","created":{"date-parts":[[2020,3,30]],"date-time":"2020-03-30T15:04:23Z","timestamp":1585580663000},"page":"3457-3480","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Bayesian network classifiers using ensembles and smoothing"],"prefix":"10.1007","volume":"62","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9851-9414","authenticated-orcid":false,"given":"He","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fran\u00e7ois","family":"Petitjean","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wray","family":"Buntine","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,3,30]]},"reference":[{"key":"1458_CR1","doi-asserted-by":"crossref","unstructured":"Bostrom H (2007) Estimating class probabilities in random forests. In: Machine learning and applications, 2007. ICMLA 2007. 6th international conference on, IEEE, pp 211\u2013216","DOI":"10.1109\/ICMLA.2007.64"},{"issue":"2","key":"1458_CR2","first-page":"123","volume":"24","author":"L Breiman","year":"1996","unstructured":"Breiman L (1996) Bagging predictors. Mach Learn 24(2):123\u2013140","journal-title":"Mach Learn"},{"issue":"1","key":"1458_CR3","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman L (2001) Random forests. Mach Learn 45(1):5\u201332","journal-title":"Mach Learn"},{"key":"1458_CR4","doi-asserted-by":"crossref","unstructured":"Buntine W (1991) Theory refinement of Bayesian networks. In: 7th conference on uncertainty in artificial intelligence, Anaheim, CA","DOI":"10.1016\/B978-1-55860-203-8.50010-3"},{"key":"1458_CR5","series-title":"Artificial intelligence frontiers in statistics","first-page":"182","volume-title":"Learning classification trees","author":"W Buntine","year":"1993","unstructured":"Buntine W (1993) Learning classification trees. Artificial intelligence frontiers in statistics. Springer, Berlin, pp 182\u2013201"},{"key":"1458_CR6","doi-asserted-by":"crossref","unstructured":"Buntine W, Mishra S (2014) Experiments with non-parametric topic models. In: Proceedings of the 20th ACM SIGKDD international conference on knowledge discovery and data mining, pp 881\u2013890","DOI":"10.1145\/2623330.2623691"},{"key":"1458_CR7","doi-asserted-by":"crossref","unstructured":"Chen T, Guestrin C (2016) XGBoost: a scalable tree boosting system. In: Proceedings of the 22nd ACM SigKDD international conference on knowledge discovery and data mining, ACM, pp 785\u2013794","DOI":"10.1145\/2939672.2939785"},{"issue":"443","key":"1458_CR8","doi-asserted-by":"publisher","first-page":"935","DOI":"10.1080\/01621459.1998.10473750","volume":"93","author":"HA Chipman","year":"1998","unstructured":"Chipman HA, George EI, McCulloch RE (1998) Bayesian CART model search. J Am Stat Assoc 93(443):935\u2013948","journal-title":"J Am Stat Assoc"},{"issue":"3","key":"1458_CR9","doi-asserted-by":"publisher","first-page":"462","DOI":"10.1109\/TIT.1968.1054142","volume":"14","author":"C Chow","year":"1968","unstructured":"Chow C, Liu C (1968) Approximating discrete probability distributions with dependence trees. IEEE Trans Inf Theory 14(3):462\u2013467","journal-title":"IEEE Trans Inf Theory"},{"key":"1458_CR10","first-page":"1177","volume":"5","author":"D Dash","year":"2004","unstructured":"Dash D, Cooper GF (2004) Model averaging for prediction with discrete Bayesian networks. J Mach Learn Res 5:1177\u20131203","journal-title":"J Mach Learn Res"},{"key":"1458_CR11","unstructured":"Du L (2011) Non-parametric Bayesian methods for structured topic models. Ph.D. thesis, Australian National University"},{"issue":"12","key":"1458_CR12","doi-asserted-by":"crossref","first-page":"651","DOI":"10.3390\/e19120651","volume":"19","author":"Z Duan","year":"2017","unstructured":"Duan Z, Wang L (2017) $$K$$-dependence Bayesian classifier ensemble. Entropy 19(12):651","journal-title":"Entropy"},{"key":"1458_CR13","unstructured":"Fayyad U, Irani K (1993) Multi-interval discretization of continuous-valued attributes for classification learning. In: Proceedings of the 13th international joint conference on artificial intelligence, pp 1022\u20131027"},{"key":"1458_CR14","doi-asserted-by":"crossref","unstructured":"Freund Y, Schapire RE (1995) A decision-theoretic generalization of on-line learning and an application to boosting. In: European conference on computational learning theory. Springer, pp 23\u201337","DOI":"10.1007\/3-540-59119-2_166"},{"issue":"2","key":"1458_CR15","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1214\/aos\/1016218223","volume":"28","author":"J Friedman","year":"2000","unstructured":"Friedman J, Hastie T, Tibshirani R et al (2000) Additive logistic regression: a statistical view of boosting (with discussion and a rejoinder by the authors). Ann Stat 28(2):337\u2013407","journal-title":"Ann Stat"},{"issue":"2\u20133","key":"1458_CR16","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1023\/A:1007465528199","volume":"29","author":"N Friedman","year":"1997","unstructured":"Friedman N, Geiger D, Goldszmidt M (1997) Bayesian network classifiers. Mach Learn 29(2\u20133):131\u2013163","journal-title":"Mach Learn"},{"issue":"4","key":"1458_CR17","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1109\/5254.708428","volume":"13","author":"MA Hearst","year":"1998","unstructured":"Hearst MA (1998) Support vector machines. IEEE Intell Syst 13(4):18\u201328","journal-title":"IEEE Intell Syst"},{"issue":"4","key":"1458_CR18","doi-asserted-by":"publisher","first-page":"382","DOI":"10.1214\/ss\/1009212519","volume":"14","author":"JA Hoeting","year":"1999","unstructured":"Hoeting JA, Madigan D, Raftery AE, Volinsky CT (1999) Bayesian model averaging: a tutorial (with comments by M. Clyde, David Draper and E. I. George, and a rejoinder by the authors). Stat Sci 14(4):382\u2013417","journal-title":"Stat Sci"},{"key":"1458_CR19","first-page":"549","volume":"5","author":"M Koivisto","year":"2004","unstructured":"Koivisto M, Sood K (2004) Exact Bayesian structure discovery in Bayesian networks. J Mach Learn Res 5:549\u2013573","journal-title":"J Mach Learn Res"},{"key":"1458_CR20","first-page":"4","volume-title":"Naive Bayes at forty: the independence assumption in information retrieval","author":"DD Lewis","year":"1998","unstructured":"Lewis DD (1998) Naive Bayes at forty: the independence assumption in information retrieval. Springer, Berlin, pp 4\u201315"},{"key":"1458_CR21","unstructured":"Lichman M (2013) UCI machine learning repository. http:\/\/archive.ics.uci.edu\/ml"},{"issue":"2","key":"1458_CR22","doi-asserted-by":"publisher","first-page":"215","DOI":"10.2307\/1403615","volume":"63","author":"D Madigan","year":"1995","unstructured":"Madigan D, York J, Allard D (1995) Bayesian graphical models for discrete data. Int Stat Rev 63(2):215\u2013232","journal-title":"Int Stat Rev"},{"key":"1458_CR23","unstructured":"Mart\u00ednez AM, Webb GI, Chen S, Zaidi NA (2016) Scalable learning of Bayesian network classifiers. J Mach Learn Res 17(1):1515\u20131549"},{"issue":"8","key":"1458_CR24","doi-asserted-by":"publisher","first-page":"1303","DOI":"10.1007\/s10994-018-5718-0","volume":"107","author":"F Petitjean","year":"2018","unstructured":"Petitjean F, Buntine W, Webb GI, Zaidi N (2018) Accurate parameter estimation for Bayesian network classifiers using hierarchical Dirichlet processes. Mach Learn 107(8):1303\u20131331","journal-title":"Mach Learn"},{"issue":"3","key":"1458_CR25","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1023\/A:1024099825458","volume":"52","author":"F Provost","year":"2003","unstructured":"Provost F, Domingos P (2003) Tree induction for probability-based ranking. Mach Learn 52(3):199\u2013215","journal-title":"Mach Learn"},{"key":"1458_CR26","first-page":"335","volume":"96","author":"M Sahami","year":"1996","unstructured":"Sahami M (1996) Learning limited dependence Bayesian classifiers. KDD 96:335\u2013338","journal-title":"KDD"},{"key":"1458_CR27","doi-asserted-by":"crossref","unstructured":"Shareghi E, Haffari G, Cohn T (2017) Compressed nonparametric language modelling. In: Proceedings of the 26th international joint conference on artificial intelligence, pp 2701\u20132707","DOI":"10.24963\/ijcai.2017\/376"},{"key":"1458_CR28","doi-asserted-by":"publisher","first-page":"158","DOI":"10.1017\/CBO9780511802478.006","volume":"1","author":"YW Teh","year":"2010","unstructured":"Teh YW, Jordan MI (2010) Hierarchical Bayesian nonparametric models with applications. Bayesian Nonparametr 1:158\u2013207","journal-title":"Bayesian Nonparametr"},{"key":"1458_CR29","unstructured":"Tian J, He R, Ram L (2010) Bayesian model averaging using the $$k$$-best Bayesian network structures. In: Proceedings of the 26th conference on uncertainty in artificial intelligence, AUAI Press, UAI\u201910, pp 589\u2013597"},{"issue":"1","key":"1458_CR30","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1007\/s10994-005-4258-6","volume":"58","author":"GI Webb","year":"2005","unstructured":"Webb GI, Boughton JR, Wang Z (2005) Not so naive Bayes: aggregating one-dependence estimators. Mach Learn 58(1):5\u201324","journal-title":"Mach Learn"},{"key":"1458_CR31","first-page":"609","volume":"1","author":"B Zadrozny","year":"2001","unstructured":"Zadrozny B, Elkan C (2001) Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers. ICML Citeseer 1:609\u2013616","journal-title":"ICML Citeseer"},{"key":"1458_CR32","doi-asserted-by":"crossref","unstructured":"Zhou ZH (2012) Ensemble methods: foundations and algorithms, 1st edn. CRC Press","DOI":"10.1201\/b12207"}],"container-title":["Knowledge and Information Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-020-01458-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10115-020-01458-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-020-01458-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,3,29]],"date-time":"2021-03-29T23:45:22Z","timestamp":1617061522000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10115-020-01458-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3,30]]},"references-count":32,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2020,9]]}},"alternative-id":["1458"],"URL":"https:\/\/doi.org\/10.1007\/s10115-020-01458-z","relation":{},"ISSN":["0219-1377","0219-3116"],"issn-type":[{"value":"0219-1377","type":"print"},{"value":"0219-3116","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,3,30]]},"assertion":[{"value":"23 July 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 February 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 February 2020","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 March 2020","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}