{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T03:20:51Z","timestamp":1740108051231,"version":"3.37.3"},"reference-count":36,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2021,11,8]],"date-time":"2021-11-08T00:00:00Z","timestamp":1636329600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,11,8]],"date-time":"2021-11-08T00:00:00Z","timestamp":1636329600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2022,3]]},"DOI":"10.1007\/s00521-021-06647-7","type":"journal-article","created":{"date-parts":[[2021,11,8]],"date-time":"2021-11-08T18:02:46Z","timestamp":1636394566000},"page":"3857-3873","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["LMSVCR: novel effective method of semi-supervised multi-classification"],"prefix":"10.1007","volume":"34","author":[{"given":"Zijie","family":"Dong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yimo","family":"Qin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8649-1538","authenticated-orcid":false,"given":"Bin","family":"Zou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuan Yan","family":"Tang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,11,8]]},"reference":[{"key":"6647_CR1","first-page":"33","volume":"18","author":"Y Altun","year":"2005","unstructured":"Altun Y, McAllester D, Belkin M (2005) Maximum margin semi-supervised learning for structured variables. Adv Neural Inf Process Syst 18:33\u201340","journal-title":"Adv Neural Inf Process Syst"},{"key":"6647_CR2","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1007\/978-3-642-36657-4_7","volume-title":"Handbook on Neural Information Processing","author":"MFA Hady","year":"2013","unstructured":"Hady MFA, Schwenker F (2013) Semi-supervised learning. Handbook on Neural Information Processing. Springer, Berlin, Heidelberg, pp 215\u2013239"},{"issue":"3","key":"6647_CR3","doi-asserted-by":"publisher","first-page":"542","DOI":"10.1109\/TNN.2009.2015974","volume":"20","author":"O Chapelle","year":"2009","unstructured":"Chapelle O, Sch\u00f6lkopf B, Zien A (2009) Semi-supervised learning. IEEE Trans Neural Netw 20(3):542\u2013542","journal-title":"IEEE Trans Neural Netw"},{"key":"6647_CR4","unstructured":"Zhu XJ (2005) Semi-supervised learning literature survey. University of Wisconsin-Madison Department of Computer Sciences"},{"key":"6647_CR5","doi-asserted-by":"publisher","first-page":"409","DOI":"10.1016\/j.neucom.2015.11.046","volume":"177","author":"Y Liu","year":"2016","unstructured":"Liu Y, Liu W, Obaid MA, Abbas IA (2016) Exponential stability of Markovian jumping cohen Cgrossberg neural networks with mixed mode-dependent time-delays. Neurocomputing 177:409\u2013415","journal-title":"Neurocomputing"},{"issue":"2","key":"6647_CR6","doi-asserted-by":"publisher","first-page":"448","DOI":"10.1016\/j.jfranklin.2015.11.013","volume":"353","author":"B Du","year":"2016","unstructured":"Du B, Liu Y, Abbas IA (2016) Existence and asymptotic behavior results of periodic solution for discrete-time neutral-type neural networks. J Franklin Institute 353(2):448\u2013461","journal-title":"J Franklin Institute"},{"key":"6647_CR7","doi-asserted-by":"publisher","first-page":"2305","DOI":"10.1007\/s00521-015-2066-x","volume":"27","author":"I Rebai","year":"2016","unstructured":"Rebai I, BenAyed Y, Mahdi W (2016) Deep multilayer multiple kernel learning. Neural Comput. Appl. 27:2305\u20132314","journal-title":"Neural Comput. Appl."},{"key":"6647_CR8","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1007\/s00521-014-1709-7","volume":"27","author":"X Li","year":"2016","unstructured":"Li X, Mao W, Jiang W (2016) Multiple-kernel-learning-based extreme learning machine for classification design. Neural Comput. Appl. 27:175\u2013184","journal-title":"Neural Comput. Appl."},{"key":"6647_CR9","doi-asserted-by":"publisher","first-page":"5889","DOI":"10.1007\/s00521-019-04065-4","volume":"32","author":"A Carballal","year":"2020","unstructured":"Carballal A, Fernandez-Lozano C, Heras J, Romero J (2020) Transfer learning features for predicting aesthetics through a novel hybrid machine learning method. Neural Comput. Appl. 32:5889\u20135900","journal-title":"Neural Comput. Appl."},{"key":"6647_CR10","first-page":"200","volume":"99","author":"T Joachims","year":"1999","unstructured":"Joachims T (1999) Transductive inference for text classification using support vector machines. Int Conf Mach Learn 99:200\u2013209","journal-title":"Int Conf Mach Learn"},{"issue":"11","key":"6647_CR11","first-page":"2399","volume":"7","author":"M Belkin","year":"2006","unstructured":"Belkin M, Niyogi P, Sindhwani V (2006) Manifold regularization: a geometric framework for learning from labeled and unlabeled examples. J Mach Learn Res 7(11):2399\u20132434","journal-title":"J Mach Learn Res"},{"key":"6647_CR12","unstructured":"Bennett K, Mangasarian OL (1999) Combining support vector and mathematical programming methods for induction. Advances in Kernel Methods-SV Learning 307\u2013326"},{"key":"6647_CR13","unstructured":"Weston J, Watkins C (1999) Support vector machines for multi-class pattern recognition. In Esann, pp. 219\u2013224"},{"issue":"465","key":"6647_CR14","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1198\/016214504000000098","volume":"99","author":"Y Lee","year":"2004","unstructured":"Lee Y, Lin Y, Wahba G (2004) Multicategory support vector machines: theory and application to the classification of microarray data and satellite radiance data. J Am Stat Assoc 99(465):67\u201381","journal-title":"J Am Stat Assoc"},{"key":"6647_CR15","doi-asserted-by":"crossref","unstructured":"Bottou L, Cortes C, Denker JS, Drucker H, Guyon I, Jackel LD, LeCun Y, Muller UA, Sackinger E, Simard P, Vapnik V (1994) Comparison of classifier methods: a case study in handwritten digit recognition. In Proceedings of the 12th IAPR International Conference on Pattern Recognition, pp. 77\u201382","DOI":"10.1109\/ICPR.1994.576879"},{"key":"6647_CR16","unstructured":"Krebel UHG (1999) Pairwise classification and support vector machines. In Advances in kernel methods: support vector learning, pp. 255\u2013268"},{"issue":"1\u20132","key":"6647_CR17","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1016\/S0925-2312(03)00435-1","volume":"55","author":"C Angulo","year":"2003","unstructured":"Angulo C, Parra X, Catala A (2003) K-SVCR. A support vector machine for multi-class classification. Neurocomputing 55(1\u20132):57\u201377","journal-title":"Neurocomputing"},{"issue":"3","key":"6647_CR18","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1090\/S0002-9947-1950-0051437-7","volume":"68","author":"N Aronszajn","year":"1950","unstructured":"Aronszajn N (1950) Theory of reproducing kernels. Trans Am Math Soc 68(3):337\u2013404","journal-title":"Trans Am Math Soc"},{"issue":"1","key":"6647_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1023\/A:1018946025316","volume":"13","author":"T Evgeniou","year":"2000","unstructured":"Evgeniou T, Pontil M, Poggio T (2000) Regularization networks and support vector machines. Adv Comput Math 13(1):1\u201350","journal-title":"Adv Comput Math"},{"key":"6647_CR20","volume-title":"Learning with kernelized elastic net regularization","author":"Y Feng","year":"2014","unstructured":"Feng Y, Yang Y, Zhao Y, Lv S, Suykens JA (2014) Learning with kernelized elastic net regularization. KU Leuven, Leuven Belgium"},{"issue":"1","key":"6647_CR21","first-page":"19","volume":"4","author":"Y Xu","year":"2014","unstructured":"Xu Y, Yang Z (2014) Elastic-net regression algorithm based on multi-scale gaussian kernel. Sci J Inf Eng 4(1):19\u201325","journal-title":"Sci J Inf Eng"},{"issue":"3\u20134","key":"6647_CR22","doi-asserted-by":"publisher","first-page":"643","DOI":"10.1016\/S0925-2312(02)00632-X","volume":"55","author":"W Wang","year":"2003","unstructured":"Wang W, Xu Z, Lu W, Zhang X (2003) Determination of the spread parameter in the Gaussian kernel for classification and regression. Neurocomputing 55(3\u20134):643\u2013663","journal-title":"Neurocomputing"},{"issue":"5","key":"6647_CR23","doi-asserted-by":"publisher","first-page":"1160","DOI":"10.1162\/0899766053491896","volume":"17","author":"Q Wu","year":"2005","unstructured":"Wu Q, Zhou DX (2005) SVM soft margin classifiers: linear programming versus quadratic programming. Neural Comput 17(5):1160\u20131187","journal-title":"Neural Comput"},{"issue":"2","key":"6647_CR24","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1007\/s10208-004-0155-9","volume":"6","author":"Q Wu","year":"2006","unstructured":"Wu Q, Ying Y, Zhou DX (2006) Learning rates of least-square regularized regression. Foundations Comput Math 6(2):171\u2013192","journal-title":"Foundations Comput Math"},{"key":"6647_CR25","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1016\/j.ins.2014.09.011","volume":"294","author":"SG Lv","year":"2015","unstructured":"Lv SG, Zhou F (2015) Optimal learning rates of $$l^{p}$$-type multiple kernel learning under general conditions. Inf Sci 294:255\u2013268","journal-title":"Inf Sci"},{"key":"6647_CR26","first-page":"1143","volume":"5","author":"DR Chen","year":"2004","unstructured":"Chen DR, Wu Q, Ying Y, Zhou DX (2004) Support vector machine soft margin classifiers: error analysis. J Mach Learn Res 5:1143\u20131175","journal-title":"J Mach Learn Res"},{"issue":"2","key":"6647_CR27","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1007\/s10208-008-9026-0","volume":"9","author":"H Tong","year":"2009","unstructured":"Tong H, Chen DR, Peng L (2009) Analysis of support vector machines regression. Foundations Comput Math 9(2):243\u2013257","journal-title":"Foundations Comput Math"},{"issue":"1\u20134","key":"6647_CR28","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1007\/s10444-004-7207-1","volume":"24","author":"DR Chen","year":"2006","unstructured":"Chen DR, Xiang DH (2006) The consistency of multicategory support vector machines. Adv Comput Math 24(1\u20134):155\u2013169","journal-title":"Adv Comput Math"},{"issue":"10","key":"6647_CR29","doi-asserted-by":"publisher","first-page":"1594","DOI":"10.1109\/TNN.2009.2027320","volume":"20","author":"H Chen","year":"2009","unstructured":"Chen H, Li L (2009) Semisupervised multicategory classification with imperfect model. IEEE Trans Neural Netw 20(10):1594\u20131603","journal-title":"IEEE Trans Neural Netw"},{"key":"6647_CR30","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1016\/j.knosys.2017.03.012","volume":"126","author":"SMH Bamakan","year":"2017","unstructured":"Bamakan SMH, Wang H, Shi Y (2017) Ramp loss k-support vector classification-regression; a robust and sparse multi-class approach to the intrusion detection problem. Knowledge-Based Syst 126:113\u2013126","journal-title":"Knowledge-Based Syst"},{"issue":"4","key":"6647_CR31","doi-asserted-by":"publisher","first-page":"1381","DOI":"10.1016\/j.asoc.2007.10.007","volume":"8","author":"CL Huang","year":"2008","unstructured":"Huang CL, Dun JF (2008) A distributed PSO CSVM hybrid system with feature selection and parameter optimization. Appl Soft Comput 8(4):1381\u20131391","journal-title":"Appl Soft Comput"},{"issue":"4","key":"6647_CR32","doi-asserted-by":"publisher","first-page":"1817","DOI":"10.1016\/j.eswa.2007.08.088","volume":"35","author":"SW Lin","year":"2008","unstructured":"Lin SW, Ying KC, Chen SC, Lee ZJ (2008) Particle swarm optimization for parameter determination and feature selection of support vector machines. Expert Syst Appl 35(4):1817\u20131824","journal-title":"Expert Syst Appl"},{"key":"6647_CR33","doi-asserted-by":"crossref","unstructured":"Qian M, Nie F, Zhang C (2009) Efficient multi-class unlabeled constrained semi-supervised SVM. In Proceedings of the 18th ACM conference on Information and knowledge management, pp. 1665\u20131668","DOI":"10.1145\/1645953.1646199"},{"key":"6647_CR34","doi-asserted-by":"crossref","unstructured":"Pan H, Kang Z (2018) Robust graph learning for semi-supervised classification. In 2018 10th International Conference on Intelligent Human-Machine Systems and Cybernetics, pp 265\u2013268","DOI":"10.1109\/IHMSC.2018.00068"},{"key":"6647_CR35","doi-asserted-by":"publisher","first-page":"196","DOI":"10.1007\/978-1-4612-4380-9_16","volume-title":"Breakthroughs in statistics","author":"F Wilcoxon","year":"1992","unstructured":"Wilcoxon F (1992) Individual comparisons by ranking methods. Breakthroughs in statistics. Springer, New York, pp 196\u2013202"},{"issue":"4","key":"6647_CR36","doi-asserted-by":"publisher","first-page":"413","DOI":"10.1007\/s102080010030","volume":"2","author":"F Cucker","year":"2002","unstructured":"Cucker F, Smale S (2002) Best choices for regularization parameters in learning theory: on the bias-variance problem. Foundations Comput Math 2(4):413\u2013428","journal-title":"Foundations Comput Math"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-021-06647-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-021-06647-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-021-06647-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,2,24]],"date-time":"2022-02-24T06:40:56Z","timestamp":1645684856000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-021-06647-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,8]]},"references-count":36,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2022,3]]}},"alternative-id":["6647"],"URL":"https:\/\/doi.org\/10.1007\/s00521-021-06647-7","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"type":"print","value":"0941-0643"},{"type":"electronic","value":"1433-3058"}],"subject":[],"published":{"date-parts":[[2021,11,8]]},"assertion":[{"value":"5 June 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 October 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 November 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest regarding the publication of this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}