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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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Библиографические подробности
Главные авторы: Anaissi, Ali, Kennedy, Paul J, Goyal, Madhu, Catchpoole, Daniel R
Формат: Artigo
Язык:Inglês
Опубликовано: BioMed Central 2013
Предметы:
Online-ссылка: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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