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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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Detalles Bibliográficos
Autores principales: Nguyen, Thanh-Tung, Huang, Joshua Zhexue, Nguyen, Thuy Thi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4387916/
https://www.ncbi.nlm.nih.gov/pubmed/25879059
http://dx.doi.org/10.1155/2015/471371