{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T19:57:56Z","timestamp":1760731076187,"version":"3.37.3"},"reference-count":42,"publisher":"Springer Science and Business Media LLC","issue":"12","license":[{"start":{"date-parts":[[2018,7,5]],"date-time":"2018-07-05T00:00:00Z","timestamp":1530748800000},"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":["Appl Intell"],"published-print":{"date-parts":[[2018,12]]},"DOI":"10.1007\/s10489-018-1225-z","type":"journal-article","created":{"date-parts":[[2018,7,5]],"date-time":"2018-07-05T04:47:51Z","timestamp":1530766071000},"page":"4551-4564","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":32,"title":["KNN-based least squares twin support vector machine for pattern classification"],"prefix":"10.1007","volume":"48","author":[{"given":"A.","family":"Mir","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1821-5037","authenticated-orcid":false,"given":"Jalal A.","family":"Nasiri","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,7,5]]},"reference":[{"issue":"3","key":"1225_CR1","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1145\/1922649.1922653","volume":"43","author":"JK Aggarwal","year":"2011","unstructured":"Aggarwal JK, Ryoo MS (2011) Human activity analysis: a review. ACM Comput Surv (CSUR) 43(3):16","journal-title":"ACM Comput Surv (CSUR)"},{"issue":"2","key":"1225_CR2","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1109\/MCSE.2010.118","volume":"13","author":"S Behnel","year":"2011","unstructured":"Behnel S, Bradshaw R, Citro C, Dalcin L, Seljebotn DS, Smith K (2011) Cython: the best of both worlds. Comput Sci Eng 13(2):31\u201339","journal-title":"Comput Sci Eng"},{"key":"1225_CR3","unstructured":"Bishop CM (2006) Pattern recognition and machine learning. Springer"},{"key":"1225_CR4","unstructured":"Cai D, He X, Zhou K, Han J, Bao H (2007) Locality sensitive discriminant analysis. In: IJCAI, vol 2007, pp 1713\u20131726"},{"key":"1225_CR5","unstructured":"Cheng G, Wan Y, Saudagar AN, Namuduri K, Buckles BP (2015) Advances in human action recognition: a survey. arXiv: 150105964"},{"issue":"3","key":"1225_CR6","first-page":"273","volume":"20","author":"C Cortes","year":"1995","unstructured":"Cortes C, Vapnik V (1995) Support-vector networks. Mach Learn 20(3):273\u2013297","journal-title":"Mach Learn"},{"key":"1225_CR7","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"},{"issue":"2","key":"1225_CR8","doi-asserted-by":"publisher","first-page":"245","DOI":"10.1007\/s10462-012-9336-0","volume":"42","author":"S Ding","year":"2014","unstructured":"Ding S, Yu J, Qi B, Huang H (2014) An overview on twin support vector machines. Artif Intell Rev 42(2):245\u2013252","journal-title":"Artif Intell Rev"},{"issue":"11","key":"1225_CR9","doi-asserted-by":"publisher","first-page":"3119","DOI":"10.1007\/s00521-016-2245-4","volume":"28","author":"S Ding","year":"2017","unstructured":"Ding S, Zhang N, Zhang X, Wu F (2017) Twin support vector machine: theory, algorithm and applications. Neural Comput and Applic 28(11):3119\u20133130","journal-title":"Neural Comput and Applic"},{"key":"1225_CR10","doi-asserted-by":"crossref","unstructured":"Golub GH, Van Loan CF (2012) Matrix computations, vol 3. JHU Press","DOI":"10.56021\/9781421407944"},{"key":"1225_CR11","unstructured":"Ho T, Kleinberg E (1996) Checkerboard dataset"},{"key":"1225_CR12","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1109\/TPAMI.2007.1068","volume":"29","author":"KR Jayadeva","year":"2007","unstructured":"Jayadeva KR, Chandra S (2007) Twin support vector machines for pattern classification. IEEE Trans Pattern Anal Mach Intell 29:5","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1225_CR13","doi-asserted-by":"crossref","unstructured":"Jayadeva KR, Chandra S (2017) Twin support vector machines: models extensions and applications. Springer Series on Computational Intelligence","DOI":"10.1007\/978-3-319-46186-1"},{"key":"1225_CR14","unstructured":"Jones E, Oliphant T, Peterson P (2014) {SciPy}: open source scientific tools for {Python}"},{"key":"1225_CR15","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1016\/j.neunet.2016.03.011","volume":"79","author":"R Khemchandani","year":"2016","unstructured":"Khemchandani R, Saigal P, Chandra S (2016) Improvements on \u03bd-twin support vector machine. Neural Netw 79:97\u2013107","journal-title":"Neural Netw"},{"key":"1225_CR16","unstructured":"Khemchandani R, Saigal P, Chandra S (2017) Angle-based twin support vector machine. Ann Oper Res, 1\u201331"},{"issue":"4","key":"1225_CR17","doi-asserted-by":"publisher","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":"2-3","key":"1225_CR18","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1007\/s11263-005-1838-7","volume":"64","author":"I Laptev","year":"2005","unstructured":"Laptev I (2005) On space-time interest points. Int J Comput Vis 64(2-3):107\u2013123","journal-title":"Int J Comput Vis"},{"key":"1225_CR19","doi-asserted-by":"crossref","unstructured":"Laptev I, Marszalek M, Schmid C, Rozenfeld B (2008) Learning realistic human actions from movies. In: IEEE Conference on computer vision and pattern recognition, 2008. CVPR 2008.IEEE, pp 1\u20138","DOI":"10.1109\/CVPR.2008.4587756"},{"issue":"1","key":"1225_CR20","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1007\/s10489-011-0314-z","volume":"37","author":"LH Lee","year":"2012","unstructured":"Lee LH, Wan CH, Rajkumar R, Isa D (2012) An enhanced support vector machine classification framework by using euclidean distance function for text document categorization. Appl Intell 37(1):80\u201399","journal-title":"Appl Intell"},{"key":"1225_CR21","unstructured":"MacQueen J et al. (1967) Some methods for classification and analysis of multivariate observations. In: Proceedings of the fifth Berkeley symposium on mathematical statistics and probability, vol 1, Oakland, pp 281\u2013297"},{"key":"1225_CR22","unstructured":"Mangasarian OL, Wild EW (2001) Proximal support vector machine classifiers. In: Proceedings KDD-2001, knowledge discovery and data mining. Citeseer"},{"issue":"1","key":"1225_CR23","doi-asserted-by":"publisher","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":"1225_CR24","unstructured":"Musicant D (1998) Ndc: normally distributed clustered datasets. Computer Sciences Department. University of Wisconsin, Madison"},{"key":"1225_CR25","doi-asserted-by":"crossref","unstructured":"Nasiri JA, Naghibzadeh M, Yazdi HS, Naghibzadeh B (2009) Ecg arrhythmia classification with support vector machines and genetic algorithm. In: Third UKSim European symposium on computer modeling and simulation, 2009. EMS\u201909. IEEE, pp 187\u2013192","DOI":"10.1109\/EMS.2009.39"},{"key":"1225_CR26","doi-asserted-by":"publisher","first-page":"248","DOI":"10.1016\/j.sigpro.2014.04.010","volume":"104","author":"JA Nasiri","year":"2014","unstructured":"Nasiri JA, Charkari NM, Mozafari K (2014) Energy-based model of least squares twin support vector machines for human action recognition. Signal Process 104:248\u2013257","journal-title":"Signal Process"},{"issue":"1","key":"1225_CR27","doi-asserted-by":"publisher","first-page":"169","DOI":"10.14257\/ijdta.2015.8.1.18","volume":"8","author":"J Nayak","year":"2015","unstructured":"Nayak J, Naik B, Behera H (2015) A comprehensive survey on support vector machine in data mining tasks: applications & challenges. Int J Datab Theory Appl 8(1):169\u2013186","journal-title":"Int J Datab Theory Appl"},{"issue":"3","key":"1225_CR28","doi-asserted-by":"publisher","first-page":"536","DOI":"10.1007\/s10489-013-0478-9","volume":"40","author":"E Owusu","year":"2014","unstructured":"Owusu E, Zhan Y, Mao QR (2014) An svm-adaboost facial expression recognition system. Appl Intell 40(3):536\u2013545","journal-title":"Appl Intell"},{"key":"1225_CR29","doi-asserted-by":"publisher","first-page":"266","DOI":"10.1016\/j.knosys.2014.08.005","volume":"71","author":"X Peng","year":"2014","unstructured":"Peng X, Chen D, Kong L (2014) A clipping dual coordinate descent algorithm for solving support vector machines. Knowl-Based Syst 71:266\u2013278","journal-title":"Knowl-Based Syst"},{"issue":"6","key":"1225_CR30","doi-asserted-by":"publisher","first-page":"976","DOI":"10.1016\/j.imavis.2009.11.014","volume":"28","author":"R Poppe","year":"2010","unstructured":"Poppe R (2010) A survey on vision-based human action recognition. Image Vis Comput 28(6):976\u2013990","journal-title":"Image Vis Comput"},{"key":"1225_CR31","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1016\/j.knosys.2017.10.008","volume":"139","author":"R Rastogi","year":"2018","unstructured":"Rastogi R, Saigal P, Chandra S (2018) Angle-based twin parametric-margin support vector machine for pattern classification. Knowl-Based Syst 139:64\u201377","journal-title":"Knowl-Based Syst"},{"key":"1225_CR32","unstructured":"Ripley BD (2007) Pattern recognition and neural networks. Cambridge University Press"},{"issue":"1","key":"1225_CR33","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1016\/j.csl.2012.06.001","volume":"27","author":"S Scherer","year":"2013","unstructured":"Scherer S, Kane J, Gobl C, Schwenker F (2013) Investigating fuzzy-input fuzzy-output support vector machines for robust voice quality classification. Comput Speech Lang 27(1):263\u2013 287","journal-title":"Comput Speech Lang"},{"key":"1225_CR34","doi-asserted-by":"crossref","unstructured":"Schuldt C, Laptev I, Caputo B (2004) Recognizing human actions: a local svm approach. In: Proceedings of the 17th International conference on pattern recognition, 2004. ICPR 2004, vol 3. IEEE, pp 32\u201336","DOI":"10.1109\/ICPR.2004.1334462"},{"issue":"6","key":"1225_CR35","doi-asserted-by":"publisher","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":"1225_CR36","unstructured":"Smola AJ, Sch\u00f6lkopf B (1998) Learning with kernels. GMD-Forschungszentrum Informationstechnik"},{"issue":"1","key":"1225_CR37","doi-asserted-by":"publisher","first-page":"174","DOI":"10.1007\/s10489-015-0751-1","volume":"45","author":"M Tanveer","year":"2016","unstructured":"Tanveer M, Khan MA, Ho SS (2016) Robust energy-based least squares twin support vector machines. Appl Intell 45(1):174\u2013186","journal-title":"Appl Intell"},{"issue":"2","key":"1225_CR38","doi-asserted-by":"publisher","first-page":"253","DOI":"10.1007\/s40745-014-0018-4","volume":"1","author":"Y Tian","year":"2014","unstructured":"Tian Y, Qi Z (2014) Review on: twin support vector machines. Ann Data Sci 1(2):253\u2013277","journal-title":"Ann Data Sci"},{"key":"1225_CR39","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1016\/j.knosys.2015.02.009","volume":"81","author":"D Tomar","year":"2015","unstructured":"Tomar D, Agarwal S (2015) A comparison on multi-class classification methods based on least squares twin support vector machine. Knowl-Based Syst 81:131\u2013147","journal-title":"Knowl-Based Syst"},{"issue":"2","key":"1225_CR40","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1109\/MCSE.2011.37","volume":"13","author":"Walt Svd","year":"2011","unstructured":"Svd Walt, Colbert SC, Varoquaux G (2011) The numpy array: a structure for efficient numerical computation. Computi Sci Eng 13(2):22\u201330","journal-title":"Computi Sci Eng"},{"issue":"4","key":"1225_CR41","doi-asserted-by":"publisher","first-page":"1041","DOI":"10.1007\/s10489-017-0984-2","volume":"48","author":"H Wang","year":"2018","unstructured":"Wang H, Zhou Z, Xu Y (2018) An improved \u03bd-twin bounded support vector machine. Appl Intell 48(4):1041\u20131053","journal-title":"Appl Intell"},{"key":"1225_CR42","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1016\/j.neunet.2012.06.010","volume":"35","author":"Q Ye","year":"2012","unstructured":"Ye Q, Zhao C, Gao S, Zheng H (2012) Weighted twin support vector machines with local information and its application. Neural Netw 35:31\u201339","journal-title":"Neural Netw"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10489-018-1225-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-018-1225-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-018-1225-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,3]],"date-time":"2023-09-03T14:45:59Z","timestamp":1693752359000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10489-018-1225-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,7,5]]},"references-count":42,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2018,12]]}},"alternative-id":["1225"],"URL":"https:\/\/doi.org\/10.1007\/s10489-018-1225-z","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"type":"print","value":"0924-669X"},{"type":"electronic","value":"1573-7497"}],"subject":[],"published":{"date-parts":[[2018,7,5]]},"assertion":[{"value":"5 July 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}