Institutional Repository [SANDBOX]
Technical University of Crete
EN  |  EL

Search

Browse

My Space

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

Zervakis Michalis, M.E. Blazadonakis

Simple record


URIhttp://purl.tuc.gr/dl/dias/02F9A884-340C-403D-82CD-69BBA151D2EF-
Identifierhttps://doi.org/10.1109/ICMLA.2007.67-
Languageen-
Extent6 pagesen
TitlePolynomial and RBF kernels as marker selection tools-a breast cancer case studyen
CreatorZervakis Michalisen
CreatorΖερβακης Μιχαληςel
CreatorM.E. Blazadonakis en
PublisherInstitute of Electrical and Electronics Engineersen
Content SummaryThe 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
Type of ItemΑφίσα σε Συνέδριοel
Type of ItemConference Posteren
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-10-24-
Date of Publication2007-
Bibliographic CitationM.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

Services

Statistics