{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T23:53:06Z","timestamp":1743119586581,"version":"3.40.3"},"publisher-location":"Cham","reference-count":10,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319220529"},{"type":"electronic","value":"9783319220536"}],"license":[{"start":{"date-parts":[[2015,1,1]],"date-time":"2015-01-01T00:00:00Z","timestamp":1420070400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2015,1,1]],"date-time":"2015-01-01T00:00:00Z","timestamp":1420070400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015]]},"DOI":"10.1007\/978-3-319-22053-6_5","type":"book-chapter","created":{"date-parts":[[2015,8,12]],"date-time":"2015-08-12T03:48:56Z","timestamp":1439351336000},"page":"43-54","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Granular Twin Support Vector Machines Based on Mixture Kernel Function"],"prefix":"10.1007","author":[{"given":"Xiuxi","family":"Wei","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huajuan","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2015,8,13]]},"reference":[{"issue":"5","key":"5_CR1","doi-asserted-by":"publisher","first-page":"905","DOI":"10.1109\/TPAMI.2007.1068","volume":"29","author":"R Jayadeva","year":"2007","unstructured":"Jayadeva, R., Reshma, K., Chandra, S.: Twin support vector machines for pattern classification. IEEE Trans. Pattern Anal. Mach. Intell. 29(5), 905\u2013910 (2007)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"5_CR2","doi-asserted-by":"crossref","unstructured":"Cong, H.H., Yang, C.F., Pu, X.R.: Efficient speaker recognition based on multi-class twin support vector machines and GMMs. In: 2008 IEEE Conference on Robotics, Automation and Mechatronics, pp. 348\u2013352 (2008)","DOI":"10.1109\/RAMECH.2008.4681433"},{"issue":"3","key":"5_CR3","first-page":"318","volume":"26","author":"XS Zhang","year":"2009","unstructured":"Zhang, X.S., Gao, X.B., Wang, Y.: Twin support vector machine for mcs detection. J. Electron. 26(3), 318\u2013325 (2009)","journal-title":"J. Electron."},{"key":"5_CR4","first-page":"149","volume":"46","author":"XS Zhang","year":"2009","unstructured":"Zhang, X.S.: Boosting twin support vector machine approach for MCs detection. Asia-Pacific Conf. Inf. Process. 46, 149\u2013152 (2009)","journal-title":"Asia-Pacific Conf. Inf. Process."},{"key":"5_CR5","doi-asserted-by":"crossref","unstructured":"Zhang, X.S., Gao, X.B.: MCs detection approach using bagging and boosting based twin support vector machine. In: 2009 IEEE International Conference on Systems, Man, and Cybernetics, San Antonio, TX, USA, pp. 5000\u20135005 (2009)","DOI":"10.1109\/ICSMC.2009.5346375"},{"issue":"23","key":"5_CR6","doi-asserted-by":"publisher","first-page":"4606","DOI":"10.1016\/j.ins.2010.07.034","volume":"180","author":"MA Kumar","year":"2010","unstructured":"Kumar, M.A., Khemchandani, R., Gopal, M., Chandra, S.: Knowledge based Least Squares Twin support vector machines. Inf. Sci. 180(23), 4606\u20134618 (2010)","journal-title":"Inf. Sci."},{"issue":"6","key":"5_CR7","first-page":"1029","volume":"48","author":"QL Ye","year":"2011","unstructured":"Ye, Q.L., Zhao, C.X., Chen, X.B.: A feature selection method for twsvm via a regularization technique. J. Comput. Res. Dev. 48(6), 1029\u20131037 (2011)","journal-title":"J. Comput. Res. Dev."},{"key":"5_CR8","doi-asserted-by":"publisher","DOI":"10.1007\/s12559-012-9179-7","author":"YT Xu","year":"2012","unstructured":"Xu, Y.T., Guo, R., Wang, L.S.: A twin multi-class classification support vetor machine. Cogn. Comput. (2012). doi:10.1007\/s12559-012-9179-7","journal-title":"Cogn. Comput."},{"key":"5_CR9","doi-asserted-by":"publisher","first-page":"486","DOI":"10.1016\/j.neucom.2012.07.012","volume":"99","author":"XJ Peng","year":"2013","unstructured":"Peng, X.J., Xu, D.: Norm-mixed twin support vector machine classifier and its geometric algorithm. Neurocomputing 99, 486\u2013495 (2013)","journal-title":"Neurocomputing"},{"key":"5_CR10","doi-asserted-by":"publisher","first-page":"999","DOI":"10.1007\/s00521-011-0791-3","volume":"22","author":"XJ Peng","year":"2013","unstructured":"Peng, X.J., Xu, D.: Robust minimum class variance twin support vector machine classifier. Neural Comput. Appl. 22, 999\u20131011 (2013)","journal-title":"Neural Comput. Appl."}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Theories and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-22053-6_5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,15]],"date-time":"2023-02-15T14:23:01Z","timestamp":1676470981000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-22053-6_5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015]]},"ISBN":["9783319220529","9783319220536"],"references-count":10,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-22053-6_5","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2015]]},"assertion":[{"value":"13 August 2015","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}