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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...
| Autores principales: | , |
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| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
Libertas Academica
2007
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2675488/ https://www.ncbi.nlm.nih.gov/pubmed/19458774 |