{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T18:05:25Z","timestamp":1768845925937,"version":"3.49.0"},"reference-count":28,"publisher":"Springer Science and Business Media LLC","issue":"S1","license":[{"start":{"date-parts":[[2012,7,10]],"date-time":"2012-07-10T00:00:00Z","timestamp":1341878400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2013,5]]},"DOI":"10.1007\/s00521-012-1041-z","type":"journal-article","created":{"date-parts":[[2012,7,9]],"date-time":"2012-07-09T11:44:01Z","timestamp":1341834241000},"page":"249-256","source":"Crossref","is-referenced-by-count":20,"title":["Constructing support vector machine ensemble with segmentation for imbalanced datasets"],"prefix":"10.1007","volume":"22","author":[{"given":"Qian","family":"Li","sequence":"first","affiliation":[]},{"given":"Bing","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Yi","family":"Li","sequence":"additional","affiliation":[]},{"given":"Naiyang","family":"Deng","sequence":"additional","affiliation":[]},{"given":"Ling","family":"Jing","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2012,7,10]]},"reference":[{"issue":"1","key":"1041_CR1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/1007730.1007733","volume":"6","author":"NV Chawla","year":"2004","unstructured":"Chawla NV, Japkowicz N, Kotcz A (2004) Editorial: special issue on learning from imbalanced data sets. SIGKDD Explor 6(1):1\u20136","journal-title":"SIGKDD Explor"},{"key":"1041_CR2","unstructured":"Japkowicz N (2000) Learning from imbalanced data sets: a comparison of various strategies. In: Proceedings of the AAAI\u20192000 workshop on learning from imbalanced data sets, pp 10\u201315"},{"key":"1041_CR3","unstructured":"Chawla NV, Japkowicz N, Kolcz A (Eds.) (2003) In: Proceedings of the ICML\u20192003 workshop on learning from imbalanced data sets"},{"key":"1041_CR4","unstructured":"Chawla NV, Japkowicz N, Zhou ZH (2009) In: PAKDD\u20192009 workshop: data mining when classes are imbalanced and errors have costs, Thailand"},{"issue":"12","key":"1041_CR5","doi-asserted-by":"crossref","first-page":"8303","DOI":"10.1016\/j.eswa.2010.05.054","volume":"37","author":"YY Nguwi","year":"2010","unstructured":"Nguwi YY, Cho SY (2010) An unsupervised self-organizing learning with support vector ranking for imbalanced datasets. Expert Syst Appl 37(12):8303\u20138312","journal-title":"Expert Syst Appl"},{"issue":"2","key":"1041_CR6","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1007\/s00521-010-0349-9","volume":"20","author":"J Tian","year":"2011","unstructured":"Tian J, Gu H, Liu WQ (2011) Imbalanced classification using support vector machine ensemble. Neural Comput Appl 20(2):203\u2013209","journal-title":"Neural Comput Appl"},{"key":"1041_CR7","unstructured":"Kubat M, Matwin S (1997) Addressing the curse of imbalanced training sets: One-sided selection. In:Proceedings of the fourteenth international conference on machine learning, pp 179\u2013186"},{"key":"1041_CR8","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1613\/jair.953","volume":"16","author":"NV Chawla","year":"2002","unstructured":"Chawla NV, Bowyer K, Hall L, Kegelmeyer WP (2002) SMOTE: synthetic minority over-sampling technique. J Artif Intell Res 16:321\u2013357","journal-title":"J Artif Intell Res"},{"key":"1041_CR9","doi-asserted-by":"crossref","unstructured":"Domingos P (1999) MetaCost: a general method for making classifiers cost sensitive. In: Proceedings of the fifth international conference on knowledge discovery and data mining, pp 155\u2013164","DOI":"10.1145\/312129.312220"},{"key":"1041_CR10","unstructured":"Elkan C (2001) The foundations of cost-sensitive learning. In: Proceedings of the seventeenth international joint conference on artificial intelligence. Morgan Kaufmann, San Francisco, pp 973\u2013978"},{"key":"1041_CR11","unstructured":"Drummond C, Holte RC (2003) C4.5, class imbalance and cost sensitivity: why under-sampling beats over-sampling. In: Workshop on Learning from Imbalanced Datasets II, held in conjunction with ICML 2003"},{"issue":"2","key":"1041_CR12","first-page":"139","volume":"2","author":"LM Manevitz","year":"2001","unstructured":"Manevitz LM, Yousef M (2001) One-class SVMs for document classification. J Mach Leran Res 2(2):139\u2013154","journal-title":"J Mach Leran Res"},{"key":"1041_CR13","doi-asserted-by":"crossref","unstructured":"Raskutti B, Kowalczyk A (2003) Extreme re-balancing for SVMs: a case study. In: Workshop on learning from imbalanced data sets II, international conference on machine learning","DOI":"10.1145\/1007730.1007739"},{"key":"1041_CR14","first-page":"273","volume":"20","author":"C Cortes","year":"1995","unstructured":"Cortes C, Vapnik V (1995) Support-vector networks. Machine Learn 20:273\u2013297","journal-title":"Machine Learn"},{"key":"1041_CR15","doi-asserted-by":"crossref","unstructured":"Deng NY, Tian YJ, Zhang CH (2012) Support vector machines: theory, algorithms, and extensions. CRC Press (in press)","DOI":"10.1201\/b14297"},{"key":"1041_CR16","unstructured":"Akbani R, Kwek S, Japkowicz N (2004) Applying support vector machines to imbalanced datasets. In: Proceedings of ECML 2004. LNCS (LNAI), 3201, pp 39\u201350"},{"key":"1041_CR17","doi-asserted-by":"crossref","unstructured":"Yang CY, Wang JJ, Yang JS and Yu GD (2008) Imbalanced SVM learning with margin compensation, In: Proceedings of ISNN 2008, Part I, LNCS 5263, pp 636\u2013644","DOI":"10.1007\/978-3-540-87732-5_71"},{"key":"1041_CR18","unstructured":"Benjamin X, Wang, Japkowicz N (2008) Boosting support vector machines for imbalanced data sets. In: Proceedings of ISMIS 2008, LNAI 4994, pp 38\u201347"},{"key":"1041_CR19","first-page":"231","volume-title":"Neural network ensembles, cross validation, and active learning. Advances in neural information processing systems 7","author":"A Krogh","year":"1995","unstructured":"Krogh A, Vedelsby J (1995) Neural network ensembles, cross validation, and active learning. Advances in neural information processing systems 7. MIT Press, Cambridge, MA, pp 231\u2013238"},{"issue":"1\u20132","key":"1041_CR20","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1016\/S0004-3702(02)00190-X","volume":"137","author":"ZH Zhou","year":"2002","unstructured":"Zhou ZH, Wu J, Tang W (2002) Ensembling neural networks: many could be better than all. Artif Intell 137(1\u20132):239\u2013263","journal-title":"Artif Intell"},{"key":"1041_CR21","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4615-3626-0","volume-title":"Vector quantization and signal compression","author":"A Gersho","year":"1992","unstructured":"Gersho A, Gray RM (1992) Vector quantization and signal compression. Kluwer, Dordrecht"},{"key":"1041_CR22","unstructured":"Yu T, Debenham J, Jan T, Simoff S (2006) Combine vector quantization and support vector machine for imbalanced datasets, In: TFTP international federation for information processing, 2006, pp 217\u2013227"},{"key":"1041_CR23","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1186\/1471-2105-9-57","volume":"9","author":"XM Zhao","year":"2008","unstructured":"Zhao XM, Wang Y, Chen LN, Kazuyuki A (2008) Gene function prediction using labeled and unlabeled data. BMC Bioinform 9:57\u201362","journal-title":"BMC Bioinform"},{"issue":"7","key":"1041_CR24","doi-asserted-by":"crossref","first-page":"897","DOI":"10.1093\/bioinformatics\/bti132","volume":"21","author":"G Dror","year":"2005","unstructured":"Dror G, Sorek R, Shamir R (2005) Accurate identification of alternatively spliced exons using support vector machine. Bioinformatics 21(7):897\u2013901","journal-title":"Bioinformatics"},{"key":"1041_CR25","unstructured":"Ning H, Yang B, Cui J, Jing L (2009) Detection of horizontal gene transfer in bacterial genomes. In: Proceedings of the third international symposium on optimization and systems biology, pp 229\u2013236"},{"key":"1041_CR26","unstructured":"Kubat M, Hotle R, Matwin S (1997) Learning when negative examples abound. In: Proceedings of the 9th European conference on machine learning. London: Springer, Heidelberg, 1224, pp 146\u2013153"},{"key":"1041_CR27","unstructured":"Hsu C-W, Chang C-C, Lin C-J (2008) A practical guide to support vector classification. http:\/\/www.csie.ntu.edu.tw\/~cjlin"},{"issue":"2","key":"1041_CR28","doi-asserted-by":"crossref","first-page":"539","DOI":"10.1109\/TSMCB.2008.2007853","volume":"39","author":"XY Liu","year":"2009","unstructured":"Liu XY, Wu JX, Zhou ZH (2009) Exploratory undersampling for class-imbalance learning. IEEE Transact Syst Man Cybern Part B Cybern 39(2):539\u2013550","journal-title":"IEEE Transact Syst Man Cybern Part B Cybern"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-012-1041-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-012-1041-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-012-1041-z","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,6,30]],"date-time":"2019-06-30T18:36:16Z","timestamp":1561919776000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-012-1041-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012,7,10]]},"references-count":28,"journal-issue":{"issue":"S1","published-print":{"date-parts":[[2013,5]]}},"alternative-id":["1041"],"URL":"https:\/\/doi.org\/10.1007\/s00521-012-1041-z","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2012,7,10]]}}}