Literature DB >> 19398451

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

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


  25 in total

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