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A balanced iterative random forest for gene selection from microarray data
BACKGROUND: The wealth of gene expression values being generated by high throughput microarray technologies leads to complex high dimensional datasets. Moreover, many cohorts have the problem of imbalanced classes where the number of patients belonging to each class is not the same. With this kind o...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2013
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3766035/ https://www.ncbi.nlm.nih.gov/pubmed/23981907 http://dx.doi.org/10.1186/1471-2105-14-261 |