Ιδρυματικό Αποθετήριο
Πολυτεχνείο Κρήτης
Πολυτεχνείο Κρήτης
EN
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| URI: | http://purl.tuc.gr/dl/dias/B7F27528-66AF-4E09-9071-85CC0196086E | ||
| Έτος | 2010 | ||
| Τύπος | Πλήρης Δημοσίευση σε Συνέδριο | ||
| Άδεια Χρήσης |
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| Βιβλιογραφική Αναφορά | I. 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.2010.5687779 https://doi.org/10.1109/ITAB.2010.5687779 | ||
| Εμφανίζεται στις Συλλογές |
Support 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.
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