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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 (...
Autores principales: | Huang, Hai-Hui, Liu, Xiao-Ying, Liang, Yong |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4852916/ https://www.ncbi.nlm.nih.gov/pubmed/27136190 http://dx.doi.org/10.1371/journal.pone.0149675 |
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