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An Empirical Study of Univariate and Genetic Algorithm-Based Feature Selection in Binary Classification with Microarray Data

BACKGROUND: We consider both univariate- and multivariate-based feature selection for the problem of binary classification with microarray data. The idea is to determine whether the more sophisticated multivariate approach leads to better misclassification error rates because of the potential to con...

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Détails bibliographiques
Auteurs principaux: Lecocke, Michael, Hess, Kenneth
Format: Artigo
Langue:Inglês
Publié: Libertas Academica 2007
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Accès en ligne:https://ncbi.nlm.nih.gov/pmc/articles/PMC2675488/
https://ncbi.nlm.nih.gov/pubmed/19458774
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