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Wrapper filtering criteria via linear neuron and kernel approaches

Zervakis Michail, Μπλαζαντωνάκης Μιχάλης Ε.

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URIhttp://purl.tuc.gr/dl/dias/AFC4CF9B-0EC4-4372-8285-746FB3A86870-
Identifierhttps://doi.org/10.1016/j.compbiomed.2008.05.005-
Identifierhttps://www.sciencedirect.com/science/article/pii/S0010482508000863?via%3Dihub-
Languageen-
Extent19 pagesen
TitleWrapper filtering criteria via linear neuron and kernel approaches en
CreatorZervakis Michailen
CreatorΖερβακης Μιχαηλel
CreatorΜπλαζαντωνάκης Μιχάλης Ε.el
CreatorBlazadonakis Michalis E.en
PublisherElsevieren
Content SummaryThe problem of marker selection in DNA microarray analysis has been addressed so far by two basic types of approaches, the so-called filter and wrapper methods. Wrapper methods operate in a recursive fashion where feature (gene) weights are re-evaluated and dynamically changing from iteration to iteration, while in filter methods feature weights remain fixed. Our objective in this study is to show that the application of filter criteria in a recursive fashion, where weights are potentially adjusted from cycle to cycle, produces noticeable improvement on the generalization performance measured on independent test sets.en
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-10-23-
Date of Publication2008-
SubjectWrapper filtering criteriaen
SubjectDNA microarray analysisen
Bibliographic CitationM. E. Blazadonakis and M. Zervakis, "Wrapper filtering criteria via linear neuron and kernel approaches," Computers Biol. Medi., vol. 38, no. 8, pp. 894-912, Aug. 2008. doi:10.1016/j.compbiomed.2008.05.005el

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