penalizedSVM: a R-package for feature selection SVM classification.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 19398451.
- Also identified by DOI 10.1093/bioinformatics/btp286.
- No licence information is recorded for this record.
- Because redistribution is not established, this page shows the abstract only. Follow the links below for the full text.
Abstract
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. The R package 'penalizedSVM' is available from the Comprehensive R Archive Network (http://cran.r-project.org/) under GPL-2 or later.
Medical subject headings
- Algorithms
- Artificial Intelligence
- Computational Biology