Regularized logistic regression without a penalty term: An application to cancer classification with microarray data-Reference-Cited by-同舟云学术

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Regularized logistic regression without a penalty term: An application to cancer classification with microarray data

Published:2011-05 Issue:5 Volume:38 Page:5110-5118
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Bielza Concha,Robles Víctor,Larrañaga Pedro

Funder

Spanish Ministry of Education and Science

Consolider Ingenio

National Institutes of Health (USA)

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference69 articles.

1. Using principal components for estimating logistic regression with high-dimensional multicollinear data;Aguilera;Computational Statistics and Data Analysis,2006

2. Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide microarrays;Alon;Proceedings of the National Academy of Sciences USA,1999

3. Effective dimension reduction methods for tumor classification using gene expression data;Antoniadis;Bioinformatics,2003

4. Algorithms for sparse linear classifier in the massive data setting;Balakrishnan;Journal of Machine Learning Research,2008

5. Supervised machine learning techniques for the classification of metabolic disorders in newborns;Baumgartner;Bioinformatics,2004

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