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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Detalles Bibliográficos
Autores principales: Lecocke, Michael, Hess, Kenneth
Formato: Texto
Lenguaje:English
Publicado: Libertas Academica 2007
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2675488/
https://www.ncbi.nlm.nih.gov/pubmed/19458774

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2675488/
https://www.ncbi.nlm.nih.gov/pubmed/19458774

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