{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T15:58:07Z","timestamp":1761580687313},"reference-count":32,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2009,5,20]],"date-time":"2009-05-20T00:00:00Z","timestamp":1242777600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Soft Comput"],"published-print":{"date-parts":[[2010,5]]},"DOI":"10.1007\/s00500-009-0434-0","type":"journal-article","created":{"date-parts":[[2009,5,19]],"date-time":"2009-05-19T10:03:38Z","timestamp":1242727418000},"page":"667-680","source":"Crossref","is-referenced-by-count":34,"title":["Adaptive pruning algorithm for least squares support vector machine classifier"],"prefix":"10.1007","volume":"14","author":[{"given":"Xiaowei","family":"Yang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"Lu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guangquan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2009,5,20]]},"reference":[{"key":"434_CR1","unstructured":"Cauwenberghs G, Poggio T (2000) Incremental and decremental support vector machine learning. In: Proceedings of advances in neural information processing systems, vol\u00a013, pp\u00a0409\u2013415"},{"issue":"1\u20133","key":"434_CR2","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1023\/A:1012450327387","volume":"46","author":"O Chapelle","year":"2002","unstructured":"Chapelle O, Vapnik V, Bousquet O, Mukherjee S (2002) Choosing kernel parameters for support vector machines. Mach Learn 46(1\u20133):131\u2013159","journal-title":"Mach Learn"},{"issue":"2","key":"434_CR3","doi-asserted-by":"crossref","first-page":"498","DOI":"10.1109\/TNN.2004.841785","volume":"16","author":"W Chu","year":"2005","unstructured":"Chu W, Ong C, Keerthi S (2005) An improved conjugate gradient scheme to the solution of least squares SVM. IEEE Trans Neural Netw 16(2):498\u2013501","journal-title":"IEEE Trans Neural Netw"},{"key":"434_CR4","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/S0167-8655(02)00190-3","volume":"24","author":"K Chua","year":"2003","unstructured":"Chua K (2003) Efficient computations for large least square support vector machine classifiers. Pattern Recognit Lett 24:75\u201380","journal-title":"Pattern Recognit Lett"},{"key":"434_CR5","first-page":"273","volume":"20","author":"C Cortes","year":"1995","unstructured":"Cortes C, Vapnik V (1995) Support-vector networks. Mach Learn 20:273\u2013297","journal-title":"Mach Learn"},{"issue":"3","key":"434_CR6","doi-asserted-by":"crossref","first-page":"696","DOI":"10.1109\/TNN.2003.810597","volume":"14","author":"B Kruif de","year":"2003","unstructured":"de Kruif B, de Vries T (2003) Pruning error minimization in least squares support vector machines. IEEE Trans Neural Netw 14(3):696\u2013702","journal-title":"IEEE Trans Neural Netw"},{"key":"434_CR7","volume-title":"Matrix computations","author":"G Golub","year":"1996","unstructured":"Golub G, Van Loan C (1996) Matrix computations, 3rd edn. The Johns Hopkins University Press, London","edition":"3"},{"key":"434_CR8","unstructured":"Hamers B, Suykens J, De Moor B (2001) A comparison of iterative methods for least squares support vector machine classifiers. ESAT-SISTA, K. U. Leuven, Leuven, Belgium, Internal Rep. 01-110"},{"key":"434_CR9","doi-asserted-by":"crossref","unstructured":"Hoegaerts L, Suykens J, Vandewalle J, De Moor B (2004) A comparison of pruning algorithms for sparse least squares support vector machines. In: Proceedings of ICONIP 2004. Lecture Notes in Computer Science, vol\u00a03316. Springer, Berlin, pp\u00a01247\u20131253","DOI":"10.1007\/978-3-540-30499-9_194"},{"key":"434_CR10","doi-asserted-by":"crossref","unstructured":"Joachims T (1998) Making large-scale support vector machine learning practical. In: Proceedings of advances in kernel methods-support vector learning. MIT Press, Cambridge, pp\u00a0169\u2013184","DOI":"10.7551\/mitpress\/1130.003.0015"},{"key":"434_CR11","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1162\/089976603762553013","volume":"15","author":"S Keerthi","year":"2003","unstructured":"Keerthi S, Shevade S (2003) SMO algorithm for least squares SVM formulations. Neural Comput 15:487\u2013507","journal-title":"Neural Comput"},{"issue":"3","key":"434_CR12","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1162\/089976601300014493","volume":"13","author":"S Keerthi","year":"2001","unstructured":"Keerthi S, Shevade S, Bhattacharyya C, Murthy K (2001) Improvements to Platt\u2019s SMO algorithm for SVM classifier design. Neural Comput 13(3):637\u2013649","journal-title":"Neural Comput"},{"issue":"5","key":"434_CR13","doi-asserted-by":"crossref","first-page":"1032","DOI":"10.1109\/72.788643","volume":"10","author":"O Mangasarian","year":"1999","unstructured":"Mangasarian O, Musicant D (1999) Successive overrelaxation for support vector machines. IEEE Transa Neural Netw 10(5):1032\u20131037","journal-title":"IEEE Transa Neural Netw"},{"key":"434_CR14","first-page":"161","volume":"1","author":"O Mangasarian","year":"2001","unstructured":"Mangasarian O, Musicant D (2001) Lagrangian support vector machines. J Mach Learn Res 1:161\u2013177","journal-title":"J Mach Learn Res"},{"key":"434_CR15","unstructured":"Murphy P, Aha D (1992) UCI repository of machine learning database. http:\/\/www.ics.uci.edu\/~mlearn\/MLRepository.html"},{"key":"434_CR16","first-page":"276","volume-title":"An improved training algorithm for support vector machines","author":"E Osuna","year":"1997","unstructured":"Osuna E, Freund R, Girosi F (1997) An improved training algorithm for support vector machines. IEEE Workshop on Neural Networks and Signal Processing, Amelia Island, pp 276\u2013285"},{"key":"434_CR17","unstructured":"Platt J (1998) Sequential minimal optimization-a fast algorithm for training support vector machines. In: Proceedings of advances in kernel methods-support vector learning. MIT Press, Cambridge, pp\u00a0185\u2013208"},{"key":"434_CR18","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9780511812651","volume-title":"Pattern recognition and neural networks","author":"B Ripley","year":"1996","unstructured":"Ripley B (1996) Pattern recognition and neural networks. Cambridge University Press, Cambridge"},{"key":"434_CR19","doi-asserted-by":"crossref","first-page":"1207","DOI":"10.1162\/089976600300015565","volume":"12","author":"B Sch\u00f6lkopf","year":"2000","unstructured":"Sch\u00f6lkopf B, Smola A, Williamson R, Bartlett P (2000) New support vector algorithms. Neural Comput 12:1207\u20131245","journal-title":"Neural Comput"},{"issue":"3","key":"434_CR20","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1023\/A:1018628609742","volume":"9","author":"J Suykens","year":"1999","unstructured":"Suykens J, Vandewalle J (1999) Least squares support vector machine classifiers. Neural Process Lett 9(3):293\u2013300","journal-title":"Neural Process Lett"},{"issue":"7","key":"434_CR21","doi-asserted-by":"crossref","first-page":"1109","DOI":"10.1109\/81.855471","volume":"47","author":"J Suykens","year":"2000","unstructured":"Suykens J, Vandewalle J (2000) Recurrent least squares support vector machines. IEEE Trans Circuits Syst I 47(7):1109\u20131114","journal-title":"IEEE Trans Circuits Syst I"},{"key":"434_CR22","unstructured":"Suykens J, Lukas L, Van Dooren P, De Moor B, Vandewalle J (1999) Least squares support vector machine classifiers: a large scale algorithm. In: Proceedings of Europe conference on circuit theory and design (ECCTD\u201999), Stresa, Italy, pp\u00a0839\u2013842"},{"key":"434_CR23","first-page":"757","volume-title":"Sparse approximation using least squares support vector machines","author":"J Suykens","year":"2000","unstructured":"Suykens J, Lukas L, Vandewalle J (2000) Sparse approximation using least squares support vector machines. IEEE International Symposium on Circuits and Systems, Genvea, Switzerland, pp 757\u2013760"},{"issue":"1","key":"434_CR24","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/S0893-6080(00)00077-0","volume":"14","author":"J Suykens","year":"2001","unstructured":"Suykens J, Vandewalle J, De Moor B (2001) Optimal control by least squares support vector machines. Neural Netw 14(1):23\u201335","journal-title":"Neural Netw"},{"issue":"1\u20134","key":"434_CR25","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/S0925-2312(01)00644-0","volume":"48","author":"J Suykens","year":"2002","unstructured":"Suykens J, De Barbanter J, Lukas L, Vandewalle J (2002a) Weighted least squares support vector machines: robustness and sparse approximation. Neurocomputing 48(1\u20134):85\u2013105","journal-title":"Neurocomputing"},{"key":"434_CR26","doi-asserted-by":"crossref","DOI":"10.1142\/5089","volume-title":"Least squares support vector machines","author":"J Suykens","year":"2002","unstructured":"Suykens J, Van Gestel T, De Brabanter J, De Moor B, Vandewalle J (2002b) Least squares support vector machines. World Scientific, Singapore"},{"issue":"4","key":"434_CR27","doi-asserted-by":"crossref","first-page":"809","DOI":"10.1109\/72.935093","volume":"12","author":"T Gestel Van","year":"2001","unstructured":"Van Gestel T et al (2001) Financial time series prediction using least squares support vector machines within the evidence framework. IEEE Trans Neural Netw 12(4):809\u2013821","journal-title":"IEEE Trans Neural Netw"},{"issue":"1","key":"434_CR28","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/B:MACH.0000008082.80494.e0","volume":"54","author":"T Gestel Van","year":"2004","unstructured":"Van Gestel T et al (2004) Benchmarking least squares support vector machine classifiers. Mach Learn 54(1):5\u201332","journal-title":"Mach Learn"},{"key":"434_CR29","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4757-2440-0","volume-title":"The nature of statistical learning theory","author":"V Vapnik","year":"1995","unstructured":"Vapnik V (1995) The nature of statistical learning theory. Springer, New York"},{"key":"434_CR30","volume-title":"Statistical learning theory","author":"V Vapnik","year":"1998","unstructured":"Vapnik V (1998) Statistical learning theory. Wiley, New York"},{"issue":"9","key":"434_CR31","doi-asserted-by":"crossref","first-page":"2013","DOI":"10.1162\/089976600300015042","volume":"12","author":"V Vapnik","year":"2000","unstructured":"Vapnik V, Chapelle O (2000) Bounds on error expectation for support vector machines. Neural Comput 12(9):2013\u20132036","journal-title":"Neural Comput"},{"issue":"6","key":"434_CR32","doi-asserted-by":"crossref","first-page":"1541","DOI":"10.1109\/TNN.2005.852239","volume":"16","author":"X Zeng","year":"2005","unstructured":"Zeng X, Chen X (2005) SMO-based pruning methods for sparse least squares support vector machines. IEEE Trans Neural Netw 16(6):1541\u20131546","journal-title":"IEEE Trans Neural Netw"}],"container-title":["Soft Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00500-009-0434-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00500-009-0434-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00500-009-0434-0","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,25]],"date-time":"2023-05-25T06:48:10Z","timestamp":1684997290000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00500-009-0434-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2009,5,20]]},"references-count":32,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2010,5]]}},"alternative-id":["434"],"URL":"https:\/\/doi.org\/10.1007\/s00500-009-0434-0","relation":{},"ISSN":["1432-7643","1433-7479"],"issn-type":[{"value":"1432-7643","type":"print"},{"value":"1433-7479","type":"electronic"}],"subject":[],"published":{"date-parts":[[2009,5,20]]}}}