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Feature Selection and Cancer Classification via Sparse Logistic Regression with the Hybrid L(1/2 +2) Regularization

Cancer classification and feature (gene) selection plays an important role in knowledge discovery in genomic data. Although logistic regression is one of the most popular classification methods, it does not induce feature selection. In this paper, we presented a new hybrid L(1/2 +2) regularization (...

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Detalhes bibliográficos
Publicado no:PLoS One
Main Authors: Huang, Hai-Hui, Liu, Xiao-Ying, Liang, Yong
Formato: Artigo
Idioma:Inglês
Publicado em: Public Library of Science 2016
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC4852916/
https://ncbi.nlm.nih.gov/pubmed/27136190
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0149675
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