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A comparative study of different machine learning methods on microarray gene expression data
BACKGROUND: Several classification and feature selection methods have been studied for the identification of differentially expressed genes in microarray data. Classification methods such as SVM, RBF Neural Nets, MLP Neural Nets, Bayesian, Decision Tree and Random Forrest methods have been used in r...
| Autores principales: | , , , |
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| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2008
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2386055/ https://www.ncbi.nlm.nih.gov/pubmed/18366602 http://dx.doi.org/10.1186/1471-2164-9-S1-S13 |