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Unbiased Feature Selection in Learning Random Forests for High-Dimensional Data

Random forests (RFs) have been widely used as a powerful classification method. However, with the randomization in both bagging samples and feature selection, the trees in the forest tend to select uninformative features for node splitting. This makes RFs have poor accuracy when working with high-di...

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Pubblicato in:ScientificWorldJournal
Autori principali: Nguyen, Thanh-Tung, Huang, Joshua Zhexue, Nguyen, Thuy Thi
Natura: Artigo
Lingua:Inglês
Pubblicazione: Hindawi Publishing Corporation 2015
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Accesso online:https://ncbi.nlm.nih.gov/pmc/articles/PMC4387916/
https://ncbi.nlm.nih.gov/pubmed/25879059
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2015/471371
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