| Literature DB >> 19398451 |
Natalia Becker1, Wiebke Werft, Grischa Toedt, Peter Lichter, Axel Benner.
Abstract
SUMMARY: Support vector machine (SVMs) classification is a widely used and one of the most powerful classification techniques. However, a major limitation is that SVM cannot perform automatic gene selection. To overcome this restriction, a number of penalized feature selection methods have been proposed. In the R package 'penalizedSVM' implemented penalization functions L(1) norm and Smoothly Clipped Absolute Deviation (SCAD) provide automatic feature selection for SVM classification tasks. AVAILABILITY: The R package 'penalizedSVM' is available from the Comprehensive R Archive Network (http://cran.r-project.org/) under GPL-2 or later.Mesh:
Year: 2009 PMID: 19398451 DOI: 10.1093/bioinformatics/btp286
Source DB: PubMed Journal: Bioinformatics ISSN: 1367-4803 Impact factor: 6.937