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A generalized-space expansion of support vector machines for diagnostic systems

Dimou Ioannis, Zervakis Michail

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URIhttp://purl.tuc.gr/dl/dias/B7F27528-66AF-4E09-9071-85CC0196086E-
Identifierhttps://doi.org/10.1109/ITAB.2010.5687779-
Identifierhttps://ieeexplore.ieee.org/document/5687779/-
Languageen-
Extent5 pagesen
TitleA generalized-space expansion of support vector machines for diagnostic systemsen
CreatorDimou Ioannisen
CreatorΔημου Ιωαννηςel
CreatorZervakis Michailen
CreatorΖερβακης Μιχαηλel
PublisherInstitute of Electrical and Electronics Engineersen
Content SummarySupport Vector Machines (SVMs) are by now an established tool used in state of the art applications in the biomedical domain. Their prevalence has unveiled both a very effective generalization capability and the inherent positive definiteness constraints in kernel selection. In this work we apply a series of composite kernel extensions stemming from nonlinear second-level kernels to standard diagnostic problems. Our aim is twofold. Firstly, to create a formulation that can accept arbitrary non-positive definite feature kernels and secondly, to allow for nonlinear second-level kernels as part of this scheme.en
Type of ItemΠλήρης Δημοσίευση σε Συνέδριοel
Type of ItemConference Full Paperen
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-10-25-
Date of Publication2010-
SubjectSupport vector machinesen
SubjectMedical diagnostic computingen
SubjectBreasten
SubjectCanceren
SubjectGeneralized-space expansionen
SubjectDiagnostic systemsen
SubjectGeneralization capabilityen
SubjectPositive definiteness constraintsen
SubjectKernel selectionen
SubjectComposite kernel extensionsen
SubjectNonlinear second-level kernelsen
Bibliographic CitationI. N. Dimou and M. E. Zervakis, "A generalized-space expansion of support vector machines for diagnostic systems," in 10th IEEE International Conference on Information Technology and Applications in Biomedicine, 2010, pp. 1-5. doi: 10.1109/ITAB.2010.5687779el

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