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Polynomial and RBF kernels as marker selection tools-a breast cancer case study

Zervakis Michalis, M.E. Blazadonakis

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URIhttp://purl.tuc.gr/dl/dias/02F9A884-340C-403D-82CD-69BBA151D2EF-
Αναγνωριστικόhttps://doi.org/10.1109/ICMLA.2007.67-
Γλώσσαen-
Μέγεθος6 pagesen
ΤίτλοςPolynomial and RBF kernels as marker selection tools-a breast cancer case studyen
ΔημιουργόςZervakis Michalisen
ΔημιουργόςΖερβακης Μιχαληςel
ΔημιουργόςM.E. Blazadonakis en
ΕκδότηςInstitute of Electrical and Electronics Engineersen
ΠερίληψηThe problem of marker selection in DNA microarray experiment, due to the "curse of dimensionality", has been mostly addressed so far by linear approaches. Taking into account the fact that the domain of interest is a complex one, where non-linear interconnections and dependencies may also exist among the extremely large number of examined genes, we address the use of nonlinear tools to assess the problem. In this study, we propose to apply the kernel ability of Support Vector Machines in combination with Fisher's ratio as an alternative approach to assess the problem.en
ΤύποςΑφίσα σε Συνέδριοel
ΤύποςConference Posteren
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2015-10-24-
Ημερομηνία Δημοσίευσης2007-
Βιβλιογραφική ΑναφοράM.E. Blazadonakis, M. Zervakis ,"Polynomial and RBF kernels as marker selection tools-a breast cancer case study ,"in 2007 Sixth Intern. Conf. on Machine Learn. and Applications, ICMLA.pp. 488-493.doi:10.1109/ICMLA.2007.67en

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