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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...

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Main Authors: Anaissi, Ali, Kennedy, Paul J, Goyal, Madhu, Catchpoole, Daniel R
Formato: Artigo
Idioma:Inglês
Publicado: BioMed Central 2013
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Acceso en liña:https://ncbi.nlm.nih.gov/pmc/articles/PMC3766035/
https://ncbi.nlm.nih.gov/pubmed/23981907
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1471-2105-14-261
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