Sparse logistic regression with a L1/2 penalty for gene selection in cancer classification-Reference-Cited by-同舟云学术

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Sparse logistic regression with a L1/2 penalty for gene selection in cancer classification

Published:2013-06-19 Issue:1 Volume:14 Page:
ISSN:1471-2105
Container-title:BMC Bioinformatics
language:en
Short-container-title:BMC Bioinformatics

Author:

Liang Yong,Liu Cheng,Luan Xin-Ze,Leung Kwong-Sak,Chan Tak-Ming,Xu Zong-Ben,Zhang Hai

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Structural Biology

Link

http://link.springer.com/content/pdf/10.1186/1471-2105-14-198.pdf

Reference33 articles.

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2. Li T, Zhang C, Ogihara M: A comparative study of feature selection and multiclass classification methods for tissue classification based on gene expression. Bioinformatics. 2004, 20: 2429-2437. 10.1093/bioinformatics/bth267.

3. Lee JW, Lee JB, Park M, Song SH: An extensive evaluation of recent classification tools applied to microarray data. Com Stat Data Anal. 2005, 48: 869-885. 10.1016/j.csda.2004.03.017.

4. Ding C, Peng H: Minimum redundancy feature selection from microarray gene expression data. J. Bioinform. Comput. 2005, 3 (2): 185-205. 10.1142/S0219720005001004.

5. Monari G, Dreyfus G: Withdrawing an example from the training set: an analytic estimation of its effect on a nonlinear parameterized model. Neurocomputing Letters. 2000, 35: 195-201. 10.1016/S0925-2312(00)00325-8.

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