{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T08:02:12Z","timestamp":1777449732274,"version":"3.51.4"},"reference-count":43,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2020,4,20]],"date-time":"2020-04-20T00:00:00Z","timestamp":1587340800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,4,20]],"date-time":"2020-04-20T00:00:00Z","timestamp":1587340800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"name":"Liaoning Province Natural Fund Project","award":["201801227"],"award-info":[{"award-number":["201801227"]}]},{"DOI":"10.13039\/501100010086","name":"Foundation of Liaoning Province Education Administration","doi-asserted-by":"crossref","award":["2017LNQN11"],"award-info":[{"award-number":["2017LNQN11"]}],"id":[{"id":"10.13039\/501100010086","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. &amp; Cyber."],"published-print":{"date-parts":[[2020,10]]},"DOI":"10.1007\/s13042-020-01124-4","type":"journal-article","created":{"date-parts":[[2020,4,20]],"date-time":"2020-04-20T16:04:18Z","timestamp":1587398658000},"page":"2371-2389","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Twin support vector machine based on adjustable large margin distribution for pattern classification"],"prefix":"10.1007","volume":"11","author":[{"given":"Liming","family":"Liu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2358-9455","authenticated-orcid":false,"given":"Maoxiang","family":"Chu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yonghui","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rongfen","family":"Gong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,4,20]]},"reference":[{"issue":"3","key":"1124_CR1","first-page":"273","volume":"20","author":"C Cortes","year":"1995","unstructured":"Cortes C, Vapnik VN (1995) Support-vector networks. Mach Learn 20(3):273\u2013297","journal-title":"Mach Learn"},{"key":"1124_CR2","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4757-3264-1","volume-title":"The nature of statistical learning theory. Translated by Zhang Xuegong","author":"VN Vapnik","year":"2000","unstructured":"Vapnik VN (2000) The nature of statistical learning theory. Translated by Zhang Xuegong. Tsinghua University Press, Beijing"},{"key":"1124_CR3","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1016\/j.eswa.2018.03.053","volume":"106","author":"B Richhariya","year":"2018","unstructured":"Richhariya B, Tanveer M (2018) EEG signal classification using universum support vector machine. Expert Syst Appl 106:169\u2013182","journal-title":"Expert Syst Appl"},{"key":"1124_CR4","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1016\/j.knosys.2016.09.032","volume":"115","author":"Q Fan","year":"2017","unstructured":"Fan Q, Wang Z, Li D, Gao D, Zha H (2017) Entropy-based fuzzy support vector machine for imbalanced datasets. Knowl Based Syst 115:87\u201399","journal-title":"Knowl Based Syst"},{"issue":"4","key":"1124_CR5","doi-asserted-by":"crossref","first-page":"4390","DOI":"10.1016\/j.eswa.2010.09.108","volume":"38","author":"J Wei","year":"2011","unstructured":"Wei J, Jian QZ, Xiang Z (2011) Face recognition method based on support vector machine and particle swarm optimization. Expert Syst Appl 38(4):4390\u20134393","journal-title":"Expert Syst Appl"},{"issue":"1\u20132","key":"1124_CR6","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1007\/s10994-005-0463-6","volume":"59","author":"GM Fung","year":"2005","unstructured":"Fung GM, Mangasarian OL (2005) Multicategory proximal support vector machine classifiers. Mach Learn 59(1\u20132):77\u201397","journal-title":"Mach Learn"},{"issue":"5","key":"1124_CR7","doi-asserted-by":"crossref","first-page":"984","DOI":"10.1109\/TPAMI.2013.178","volume":"36","author":"X Huang","year":"2014","unstructured":"Huang X, Shi L, Suykens JAK (2014) Support vector machine classifier with pinball loss. IEEE Trans Pattern Anal Mach Intell 36(5):984\u2013997","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1124_CR8","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/j.spl.2017.09.006","volume":"132","author":"X Lu","year":"2018","unstructured":"Lu X, Dong F, Liu X, Chang X (2018) Varying coefficient support vector machines. Stat Probabil Lett 132:107\u2013115","journal-title":"Stat Probabil Lett"},{"key":"1124_CR9","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1016\/j.patcog.2016.02.018","volume":"59","author":"D Wang","year":"2016","unstructured":"Wang D, Zhang X, Fan M, Ye X (2016) Hierarchical mixing linear support vector machines for nonlinear classification. Pattern Recognit 59:255\u2013267","journal-title":"Pattern Recognit"},{"issue":"2","key":"1124_CR10","doi-asserted-by":"crossref","first-page":"464","DOI":"10.1109\/72.991432","volume":"13","author":"CF Lin","year":"2002","unstructured":"Lin CF, Wang SD (2002) Fuzzy support vector machines. IEEE Trans Neural Netw 13(2):464\u2013471","journal-title":"IEEE Trans Neural Netw"},{"issue":"6","key":"1124_CR11","doi-asserted-by":"crossref","first-page":"703","DOI":"10.1007\/s13042-012-0132-6","volume":"4","author":"R Khemchandani","year":"2013","unstructured":"Khemchandani R, Karpatne A, Chandra S (2013) Proximal support tensor machines. Int J Mach Learn Cybern 4(6):703\u2013712","journal-title":"Int J Mach Learn Cybern"},{"issue":"6","key":"1124_CR12","doi-asserted-by":"crossref","first-page":"1204","DOI":"10.1109\/TPAMI.2015.2477830","volume":"38","author":"G Loosli","year":"2016","unstructured":"Loosli G, Canu S, Ong CS (2016) Learning SVM in Krein spaces. IEEE Trans Pattern Anal Mach Intell 38(6):1204\u20131216","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"5","key":"1124_CR13","doi-asserted-by":"crossref","first-page":"905","DOI":"10.1109\/TPAMI.2007.1068","volume":"29","author":"Khemchandani R Jayadeva","year":"2007","unstructured":"Jayadeva Khemchandani R, Chandra S (2007) Twin support vector machines for pattern classification. IEEE Trans Pattern Anal Mach Intell 29(5):905\u2013910","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"1","key":"1124_CR14","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1109\/TPAMI.2006.17","volume":"28","author":"OL Mangasarian","year":"2006","unstructured":"Mangasarian OL, Wild EW (2006) Multisurface proximal support vector machine classification via generalized eigenvalues. IEEE Trans Pattern Anal Mach Intell 28(1):69\u201374","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1124_CR15","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1016\/j.neunet.2014.06.007","volume":"57","author":"HY Yang","year":"2014","unstructured":"Yang HY, Wang XY, Niu PP, Liu YC (2014) Image denoising using nonsubsampled shearlet transform and twin support vector machines. Neural Netw 57:152\u2013165","journal-title":"Neural Netw"},{"key":"1124_CR16","doi-asserted-by":"crossref","unstructured":"Ding M, Yang D, Li X (2013) Fault diagnosis for wireless sensor by twin support vector machine. Math Probl Eng 2013","DOI":"10.1155\/2013\/718783"},{"key":"1124_CR17","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1016\/j.chemolab.2017.10.020","volume":"171","author":"M Chu","year":"2017","unstructured":"Chu M, Gong R, Gao S, Zhao J (2017) Steel surface defects recognition based on multi-type statistical features and enhanced twin support vector machine. Chemometr Intell Lab 171:140\u2013150","journal-title":"Chemometr Intell Lab"},{"issue":"4","key":"1124_CR18","doi-asserted-by":"crossref","first-page":"7535","DOI":"10.1016\/j.eswa.2008.09.066","volume":"36","author":"MA Kumar","year":"2009","unstructured":"Kumar MA, Gopal M (2009) Least squares twin support vector machines for pattern classification. Expert Syst Appl 36(4):7535\u20137543","journal-title":"Expert Syst Appl"},{"issue":"6","key":"1124_CR19","doi-asserted-by":"crossref","first-page":"962","DOI":"10.1109\/TNN.2011.2130540","volume":"22","author":"YH Shao","year":"2011","unstructured":"Shao YH, Zhang CH, Wang XB, Deng NY (2011) Improvements on twin support vector machines. IEEE Trans Neural Netw 22(6):962\u2013968","journal-title":"IEEE Trans Neural Netw"},{"key":"1124_CR20","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.patcog.2017.02.011","volume":"67","author":"S Ding","year":"2017","unstructured":"Ding S, Zhang X, An Y, Xue Y (2017) Weighted linear loss multiple birth support vector machine based on information granulation for multi-class classification. Pattern Recognit 67:32\u201346","journal-title":"Pattern Recognit"},{"issue":"7","key":"1124_CR21","doi-asserted-by":"crossref","first-page":"1067","DOI":"10.1109\/TCYB.2013.2279167","volume":"44","author":"Y Tian","year":"2014","unstructured":"Tian Y, Qi Z, Ju X, Liu X (2014) Nonparallel support vector machines for pattern classification. IEEE Trans Cybern 44(7):1067\u20131079","journal-title":"IEEE Trans Cybern"},{"issue":"2","key":"1124_CR22","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1109\/TNNLS.2015.2513006","volume":"28","author":"Y Xu","year":"2017","unstructured":"Xu Y, Yang Z, Pan X (2017) A novel twin support-vector machine with pinball loss. IEEE Trans Neural Netw Learn Syst 28(2):359\u2013370","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"1124_CR23","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.ins.2012.09.009","volume":"221","author":"X Peng","year":"2013","unstructured":"Peng X, Xu D (2013) A twin-hypersphere support vector machine classifier and the fast learning algorithm. Inf Sci 221:12\u201327","journal-title":"Inf Sci"},{"key":"1124_CR24","doi-asserted-by":"crossref","unstructured":"Freund Y, Schapire RE (1995) A decision-theoretic generalization of on-line learning and an application to boosting. In: Proceedings of the 2nd European conference on computational learning theory, pp 23\u201337","DOI":"10.1007\/3-540-59119-2_166"},{"issue":"7","key":"1124_CR25","doi-asserted-by":"crossref","first-page":"1493","DOI":"10.1162\/089976699300016106","volume":"11","author":"L Breiman","year":"1999","unstructured":"Breiman L (1999) Prediction games and arcing classifiers. Neural Comput 11(7):1493\u20131517","journal-title":"Neural Comput"},{"key":"1124_CR26","doi-asserted-by":"crossref","unstructured":"Reyzin L, Schapire RE (2006) How boosting the margin can also boost classifier complexity. In: Proceedings of the 23rd international conference on Machine learning, ACM, pp 753\u2013760","DOI":"10.1145\/1143844.1143939"},{"issue":"5","key":"1124_CR27","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.artint.2013.07.002","volume":"203","author":"W Gao","year":"2013","unstructured":"Gao W, Zhou Z (2013) On the doubt about margin explanation of boosting. Artif Intell 203(5):1\u201318","journal-title":"Artif Intell"},{"key":"1124_CR28","doi-asserted-by":"crossref","unstructured":"Zhang T, Zhou ZH (2014) Large margin distribution machine. In: Proceedings of ACM SIGKDD international conference on knowledge discovery and data mining, ACM, vol 20, pp 313\u2013322","DOI":"10.1145\/2623330.2623710"},{"issue":"7","key":"1124_CR29","doi-asserted-by":"crossref","first-page":"1749","DOI":"10.1109\/TKDE.2016.2535283","volume":"28","author":"YH Zhou","year":"2016","unstructured":"Zhou YH, Zhou ZH (2016) Large margin distribution learning with cost interval and unlabeled data. IEEE Trans Knowl Data Eng 28(7):1749\u20131763","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"1124_CR30","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.patrec.2017.01.010","volume":"88","author":"F Cheng","year":"2017","unstructured":"Cheng F, Zhang J, Li Z, Tang M (2017) Double distribution support vector machine. Pattern Recognit Lett 88:20\u201325","journal-title":"Pattern Recognit Lett"},{"key":"1124_CR31","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1016\/j.patrec.2017.09.005","volume":"98","author":"S Abe","year":"2017","unstructured":"Abe S (2017) Unconstrained large margin distribution machines. Pattern Recognit Lett 98:96\u2013102","journal-title":"Pattern Recognit Lett"},{"key":"1124_CR32","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/j.neucom.2016.10.053","volume":"224","author":"F Cheng","year":"2017","unstructured":"Cheng F, Zhang J, Wen C, Liu Z, Li Z (2017) Large cost-sensitive margin distribution machine for imbalanced data classification. Neurocomputing 224:45\u201357","journal-title":"Neurocomputing"},{"key":"1124_CR33","doi-asserted-by":"crossref","DOI":"10.1201\/b14297","volume-title":"Support vector machines optimization based theory, algorithms and extensions","author":"N Deng","year":"2012","unstructured":"Deng N, Tian Y, Zhang C (2012) Support vector machines optimization based theory, algorithms and extensions. Chapman and Hall\/\/CRC, London"},{"issue":"5","key":"1124_CR34","first-page":"949","volume":"31","author":"HX Cheng","year":"2016","unstructured":"Cheng HX, Wang J (2016) A novel twin large margin distribution machine. Control Decis 31(5):949\u2013954","journal-title":"Control Decis"},{"key":"1124_CR35","doi-asserted-by":"crossref","unstructured":"Qing W, Qi SW, Sun KY (2017) Weighted least squares twin large margin distribution machine. In: Proceedings of the 2017 VI international conference on network, communication and computing. ACM, pp 253\u2013257","DOI":"10.1145\/3171592.3171638"},{"key":"1124_CR36","first-page":"718","volume-title":"Australasian joint conference on artificial intelligence","author":"H Xu","year":"2018","unstructured":"Xu H, McCane B, Szymanski L (2018) Twin bounded large margin distribution machine. Australasian joint conference on artificial intelligence. Springer, Cham, pp 718\u2013729"},{"key":"1124_CR37","unstructured":"Dua D, Taniskidou EK. UCI machine learning repository. [Online]. Available: http:\/\/archive.ics.uci.edu\/ml\/"},{"key":"1124_CR38","first-page":"1","volume":"7","author":"J Dem\u0161ar","year":"2006","unstructured":"Dem\u0161ar J (2006) Statistical comparisons of classifiers over multiple data sets. J Mach Learn Res 7:1\u201330","journal-title":"J Mach Learn Res"},{"key":"1124_CR39","unstructured":"Nemenyi P (1963) Distribution-free multiple comparisons. https:\/\/books.google.fi\/books?id=nhDMtgAACAAJ"},{"key":"1124_CR40","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.knosys.2015.08.009","volume":"88","author":"X Pan","year":"2015","unstructured":"Pan X, Luo Y, Xu Y (2015) K-nearest neighbor based structural twin support vector machine. Knowl Based Syst 88:34\u201344","journal-title":"Knowl Based Syst"},{"key":"1124_CR41","unstructured":"USPS Digit Dataset. [online]. Available: https:\/\/www.csie.ntu.edu.tw\/"},{"key":"1124_CR42","doi-asserted-by":"crossref","first-page":"858","DOI":"10.1016\/j.apsusc.2013.09.002","volume":"285","author":"K Song","year":"2013","unstructured":"Song K, Yan Y (2013) A noise robust method based on completed local binary patterns for hot-rolled steel strip surface defects. Appl Surf Sci 285:858\u2013864","journal-title":"Appl Surf Sci"},{"key":"1124_CR43","unstructured":"Everingham M, Van\u2009~\u2009Gool L, Williams CKI, Winn J, Zisserman A (2012) The PASCAL visual object classes challenge 2012 (VOC2012) Results; 2012 [cited 2012 February]. Available: http:\/\/www.pascalnetwork.org\/challenges\/VOC\/voc2012\/workshop\/index.html"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-020-01124-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13042-020-01124-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-020-01124-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,4,19]],"date-time":"2021-04-19T23:55:05Z","timestamp":1618876505000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13042-020-01124-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,4,20]]},"references-count":43,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2020,10]]}},"alternative-id":["1124"],"URL":"https:\/\/doi.org\/10.1007\/s13042-020-01124-4","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"value":"1868-8071","type":"print"},{"value":"1868-808X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,4,20]]},"assertion":[{"value":"4 March 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 April 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 April 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}