{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,2]],"date-time":"2026-08-02T04:38:29Z","timestamp":1785645509517,"version":"3.56.0"},"publisher-location":"Boston, MA","reference-count":27,"publisher":"Springer US","isbn-type":[{"value":"9781489976857","type":"print"},{"value":"9781489976871","type":"electronic"}],"license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"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":[],"published-print":{"date-parts":[[2017]]},"DOI":"10.1007\/978-1-4899-7687-1_252","type":"book-chapter","created":{"date-parts":[[2019,3,20]],"date-time":"2019-03-20T20:09:45Z","timestamp":1553112585000},"page":"393-402","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Ensemble Learning"],"prefix":"10.1007","author":[{"given":"Gavin","family":"Brown","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2017,4,14]]},"reference":[{"issue":"2","key":"252_CR514","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":"252_CR515","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":"252_CR516","unstructured":"Brown G (2004) Diversity in neural network ensembles. PhD thesis, University of Birmingham"},{"issue":"1","key":"252_CR517","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1016\/j.inffus.2004.04.004","volume":"6","author":"G Brown","year":"2005","unstructured":"Brown G, Wyatt JL, Harris R, Yao X (2005) Diversity creation methods: a survey and categorisation. J Inf Fusion 6(1):5\u201320","journal-title":"J Inf Fusion"},{"key":"252_CR518","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1145\/1143844.1143865","volume-title":"Proceedings of the 23rd international conference on machine learning","author":"R Caruana","year":"2006","unstructured":"Caruana R, Niculescu-Mizil A (2006) An empirical comparison of supervised learning algorithms. In: Proceedings of the 23rd international conference on machine learning. ACM, New York, pp\u00a0161\u2013168"},{"key":"252_CR519","first-page":"148","volume-title":"Proceedings of the thirteenth international conference on machine learning (ICML\u201996)","author":"Y Freund","year":"1996","unstructured":"Freund Y, Schapire R (1996) Experiments with a new boosting algorithm. In: Proceedings of the thirteenth international conference on machine learning (ICML\u201996). Morgan Kauffman Publishers, San Francisco, pp\u00a0148\u2013156"},{"issue":"1","key":"252_CR520","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1162\/neco.1992.4.1.1","volume":"4","author":"S Geman","year":"1992","unstructured":"Geman S, Bienenstock E, Doursat R (1992) Neural networks and the bias\/variance dilemma. Neural Comput 4(1):1\u201358","journal-title":"Neural Comput"},{"issue":"8","key":"252_CR521","doi-asserted-by":"publisher","first-page":"832","DOI":"10.1109\/34.709601","volume":"20","author":"TK Ho","year":"1998","unstructured":"Ho TK (1998) The random subspace method for constructing decision forests. IEEE Trans Pattern Anal Mach Intell 20(8):832\u2013844","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"1","key":"252_CR522","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1162\/neco.1991.3.1.79","volume":"3","author":"RA Jacobs","year":"1991","unstructured":"Jacobs RA, Jordan MI, Nowlan SJ, Hinton GE (1991) Adaptive mixtures of local experts. Neural Comput 3(1):79\u201387","journal-title":"Neural Comput"},{"key":"252_CR523","unstructured":"Kearns M, Valiant LG (1988) Learning Boolean formulae or finite automata is as hard as factoring. Technical report TR-14-88, Harvard University Aiken Computation Laboratory"},{"issue":"4","key":"252_CR524","doi-asserted-by":"publisher","first-page":"1455","DOI":"10.1214\/009053605000000228","volume":"33","author":"V Koltchinskii","year":"2005","unstructured":"Koltchinskii V, Panchenko D (2005) Complexities of convex combinations and bounding the generalization error in classification. Ann Stat 33(4):1455","journal-title":"Ann Stat"},{"key":"252_CR525","first-page":"231","volume-title":"Advances in neural information processing systems","author":"A Krogh","year":"1995","unstructured":"Krogh A, Vedelsby J (1995) Neural network ensembles, crossvalidation and active learning. In: Advances in neural information processing systems. MIT Press, Cambridge, pp\u00a0231\u2013238"},{"key":"252_CR526","doi-asserted-by":"crossref","unstructured":"Kuncheva LI (2004a) Classifier ensembles for changing environments. In: International workshop on multiple classifier systems. Lecture notes in computer science, vol\u00a03007. Springer, Berlin","DOI":"10.1007\/978-3-540-25966-4_1"},{"key":"252_CR527","doi-asserted-by":"publisher","DOI":"10.1002\/0471660264","volume-title":"Combining pattern classifiers: methods and algorithms","author":"LI Kuncheva","year":"2004","unstructured":"Kuncheva LI (2004b) Combining pattern classifiers: methods and algorithms. Wiley, New York"},{"key":"252_CR528","volume-title":"Deuxieme supplement a la theorie analytique des probabilites","author":"PS Laplace","year":"1818","unstructured":"Laplace PS (1818) Deuxieme supplement a la theorie analytique des probabilites. Gauthier-Villars, Paris"},{"key":"252_CR529","first-page":"131","volume":"9","author":"D Mease","year":"2008","unstructured":"Mease D, Wyner A (2008) Evidence contrary to the statistical view of Boosting. J Mach Learn Res 9:131\u2013156","journal-title":"J Mach Learn Res"},{"issue":"1","key":"252_CR530","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1016\/j.inffus.2004.04.001","volume":"6","author":"P Melville","year":"2005","unstructured":"Melville P, Mooney RJ (2005) Creating diversity in ensembles using artificial data. Inf Fusion 6(1):99\u2013111","journal-title":"Inf Fusion"},{"issue":"3","key":"252_CR531","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1109\/MCAS.2006.1688199","volume":"6","author":"R Polikar","year":"2006","unstructured":"Polikar R (2006) Ensemble based systems in decision making. IEEE Circ Syst Mag 6(3):21\u201345","journal-title":"IEEE Circ Syst Mag"},{"issue":"9","key":"252_CR532","doi-asserted-by":"publisher","first-page":"1184","DOI":"10.1109\/TPAMI.2002.1033211","volume":"24","author":"G R\u00e4tsch","year":"2002","unstructured":"R\u00e4tsch G, Mika S, Sch\u00f6lkopf B, M\u00fcller KR (2002) Constructing Boosting algorithms from SVMs: an application to one-class classification. IEEE Trans Pattern Anal Mach Intell 24(9):1184\u20131199","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"10","key":"252_CR533","doi-asserted-by":"publisher","first-page":"1619","DOI":"10.1109\/TPAMI.2006.211","volume":"28","author":"J Rodriguez","year":"2006","unstructured":"Rodriguez J, Kuncheva L, Alonso C (2006) Rotation forest: a new classifier ensemble method. IEEE Trans Pattern Anal Mach Intell 28(10):1619\u20131630","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"252_CR534","unstructured":"Roli F, Kittler J, Windridge D, Oza N, Polikar R, Haindl M et\u00a0al (eds) Proceedings of the international workshop on multiple classifier systems 2000\u20132009. Lecture notes in computer science. Springer, Berlin. Available at: http:\/\/www.informatik.uni-trier.de\/ley\/db\/conf\/mcs\/index.html"},{"key":"252_CR535","first-page":"197","volume":"5","author":"RE Schapire","year":"1990","unstructured":"Schapire RE (1990) The strength of weak learnability. Mach Learn 5:197\u2013227","journal-title":"Mach Learn"},{"key":"252_CR536","first-page":"1401","volume-title":"Proceedings of the 16th international joint conference on artificial intelligence","author":"RE Schapire","year":"1999","unstructured":"Schapire RE (1999) A brief introduction to boosting. In: Proceedings of the 16th international joint conference on artificial intelligence. Morgan Kaufmann, San Francisco, pp\u00a01401\u20131406"},{"key":"252_CR537","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1007\/978-0-387-21579-2_9","volume-title":"Nonlinear estimation & classification Lecture notes in statistics","author":"RE Schapire","year":"2003","unstructured":"Schapire RE (2003) The boosting approach to machine learning: an overview. In: Denison DD, Hansen MH, Holmes C, Mallick B, Yu B (eds) Nonlinear estimation & classification Lecture notes in statistics. Springer, Berlin, pp\u00a0149\u2013172"},{"key":"252_CR538","first-page":"583","volume":"3","author":"A Strehl","year":"2003","unstructured":"Strehl A, Ghosh J (2003) Cluster ensembles \u2013 a knowledge reuse framework for combining multiple partitions. J Mach Learn Res 3:583\u2013617","journal-title":"J Mach Learn Res"},{"issue":"3\u20134","key":"252_CR539","doi-asserted-by":"publisher","first-page":"385","DOI":"10.1080\/095400996116839","volume":"8","author":"K Tumer","year":"1996","unstructured":"Tumer K, Ghosh J (1996) Error correlation and error reduction in ensemble classifiers. Connect Sci 8(3\u20134):385\u2013403","journal-title":"Connect Sci"},{"key":"252_CR540","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1109\/ICNN.1996.548872","volume":"1","author":"N Ueda","year":"1996","unstructured":"Ueda N, Nakano R (1996) Generalization error of ensemble estimators. In: Proceedings of IEEE international conference on neural networks, vol\u00a01, pp\u00a090\u201395. ISBN:0-7803-3210-5","journal-title":"Proceedings of IEEE international conference on neural networks"}],"container-title":["Encyclopedia of Machine Learning and Data Mining"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-1-4899-7687-1_252","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,14]],"date-time":"2022-09-14T02:26:40Z","timestamp":1663122400000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-1-4899-7687-1_252"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"ISBN":["9781489976857","9781489976871"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-1-4899-7687-1_252","relation":{},"subject":[],"published":{"date-parts":[[2017]]},"assertion":[{"value":"14 April 2017","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}