Feature Selection and Cancer Classification via Sparse Logistic Regression with the Hybrid L1/2 +2 Regularization.

Feature Selection and Cancer Classification via Sparse Logistic Regression with the Hybrid L1/2 +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 L1/2 +2 regularization (HL...

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Bibliographic Details
Main Authors:	Hai-Hui Huang, Xiao-Ying Liu, Yong Liang
Format:	Article
Language:	English
Published:	Public Library of Science (PLoS) 2016-01-01
Series:	PLoS ONE
Online Access:	http://europepmc.org/articles/PMC4852916?pdf=render

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