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Type I Error Control for Tree Classification

Binary tree classification has been useful for classifying the whole population based on the levels of outcome variable that is associated with chosen predictors. Often we start a classification with a large number of candidate predictors, and each predictor takes a number of different cutoff values...

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Detalhes bibliográficos
Publicado no:Cancer Inform
Main Authors: Jung, Sin-Ho, Chen, Yong, Ahn, Hongshik
Formato: Artigo
Idioma:Inglês
Publicado em: Libertas Academica 2014
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC4237155/
https://ncbi.nlm.nih.gov/pubmed/25452689
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.4137/CIN.S16342
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