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Please use this identifier to cite or link to this item: https://doi.org/10.1109/CDC.2007.4434191
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dc.titleHigh performance quadratic classifier and the application on PenDigits recognition
dc.contributor.authorZhao, Z.J.
dc.contributor.authorSun, J.
dc.contributor.authorGe, S.S.
dc.date.accessioned2013-10-09T06:19:33Z
dc.date.available2013-10-09T06:19:33Z
dc.date.issued2007
dc.identifier.citationZhao, Z.J.,Sun, J.,Ge, S.S. (2007). High performance quadratic classifier and the application on PenDigits recognition. Proceedings of the IEEE Conference on Decision and Control : 3072-3077. ScholarBank@NUS Repository. <a href="https://doi.org/10.1109/CDC.2007.4434191" target="_blank">https://doi.org/10.1109/CDC.2007.4434191</a>
dc.identifier.isbn1424414989
dc.identifier.issn01912216
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/44241
dc.description.abstractA nonconvex quadratic classifier is proposed for pattern recognition. The classifier is obtained by solving a second-order cone optimization problem on the training data set. Numerical results are presented to compare this classifier with the Gaussian classifier and k-NN classifiers. Regarding to the application of hand written digits recognition, the computational result shows that the proposed quadratic classifier always achieves highest correctness in the testing stage although it takes the longest computational time in the training stage. © 2007 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/CDC.2007.4434191
dc.sourceScopus
dc.subjectPattern recognition
dc.subjectPen-digit recognition
dc.subjectQuadratic programming
dc.subjectSecond-order cone optimization
dc.typeConference Paper
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.contributor.departmentDECISION SCIENCES
dc.description.doi10.1109/CDC.2007.4434191
dc.description.sourcetitleProceedings of the IEEE Conference on Decision and Control
dc.description.page3072-3077
dc.description.codenPCDCD
dc.identifier.isiutNOT_IN_WOS
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