penalizedSVM: a R-package for feature selection SVM classification.
CONCLUSIONS
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.


BACKGROUND
The R package 'penalizedSVM' is available from the Comprehensive R Archive Network (http://cran.r-project.org/) under GPL-2 or later.
Becker
Natalia
N
Division Molecular Genetics and Division Biostatistics, Heidelberg, Germany. natalia.becker@dkfz.de
Werft
Wiebke
W
Toedt
Grischa
G
Lichter
Peter
P
Benner
Axel
A
D000465:Algorithms; D001185:Artificial Intelligence; D002965:Classification / Q000379:methods; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D020869:Gene Expression Profiling / Q000379:methods; D053263:Gene Regulatory Networks; D012984:Software